Tm-ENHANCED BLOCKING OLIGONUCLEOTIDES AND BAITS FOR IMPROVED TARGET ENRICHMENT AND REDUCED OFF-TARGET SELECTION

ABSTRACT

The invention is directed to modified oligonucleotide compositions and methods for selectively reducing unwanted nucleic acid contaminants and enriching for desired nucleic acid targets from complex genomic nucleic acid mixtures for sequencing applications. The modified oligonucleotide compositions include one or more modified groups that increase the T m  of the resultant oligonucleotide composition.

CROSS-REFERENCE TO RELATED APPLICATIONS

[01] This application is a divisional of U.S. patent application Ser.No. 13/935,451, filed Jul. 3, 2013, which claims benefit of priorityunder 35 U.S.C. 119 from U.S. Provisional Application No. 61/667,919,filed Jul. 3, 2012 and entitled “METHODS AND COMPOSITIONS FOR REDUCINGOFF-TARGET SELECTION” and U.S. Provisional Application No. 61/745,435,filed Dec. 21, 2012 and entitled “T_(M)-ENHANCED BLOCKINGOLIGONUCLEOTIDES AND BAITS FOR IMPROVED TARGET ENRICHMENT IN MASSIVELYPARALLEL SEQUENCING EXPERIMENTS,” the contents of which are incorporatedby reference herein in their entireties.

SEQUENCE LISTING

The SEQ ID NOs. disclosed herein are included in the Sequence Listingfound at the end of the specification and are included in a computerreadable form entitled “IDT01-001-US_CORRECTED_ST25.txt,” created onSep. 3, 2013 and having a file size of 48,259 bytes, filed by electronicmeans via the EFS-Web e-filing system, the contents of which areincorporated by reference in its entirety.

FIELD OF THE INVENTION

This invention relates to modified oligonucleotide compositions andtheir use in methods for nucleic acid selection and sequencing. Inparticular, the invention pertains to T_(m)-enhanced oligonucleotides asblockers and baits, as well as other reagents for improved targetenrichment and reduced off-target selection. The oligonucleotidecompositions and reagents find robust applications for preparing nucleicacid templates for next generation sequencing applications.

BACKGROUND OF THE INVENTION

Nucleic acid hybridization has a significant role in biotechnologyapplications pertaining to identification, selection, and sequencing ofnucleic acids. Sequencing applications with genomic nucleic acids as thetarget materials demand one to select nucleic acid targets of interestfrom a highly complex mixture. The quality of the sequencing effortsdepends on the efficiency of the selection process, which, in turn,relies upon how well nucleic acid targets can be enriched relative tonon-target sequences.

A variety of methods have been used to enrich for desired sequences froma complex pool of nucleic acids, such as genomic DNA or cDNA. Thesemethods include the polymerase chain reaction (PCR), molecular inversionprobes (MIPs), or sequence capture by hybrid formation (“hybridcapture;” See, for example, Mamanova, L., Coffey, A. J., Scott, C. E.,Kozarewa, I., Turner, E. H., Kumar, A., Howard, E., Shendure, J. andTurner, D. J. (2010) “Target-enrichment strategies for next-generationsequencing,” Nat. Methods 7:111-118.). Hybrid capture offers advantagesover other methods in that this method requires fewer enzymaticamplification or manipulation procedures of the target nucleic acid ascompared to the other methods. The hybrid capture method introducesfewer errors into the final sequencing library as a result. For thisreason, the hybrid capture method is a preferred method for enrichingfor desired sequences from a complex pool of nucleic acids and is idealfor preparing templates in next generation sequencing (NGS)applications.

The NGS applications usually involve randomly breaking long genomic DNAor cDNA into smaller fragment sizes having a size distribution of200-500 bp in length, depending upon the NGS platform used. The DNAtermini are enzymatically treated to facilitate ligation and universalDNA adaptors are ligated to the ends to provide the resultant NGStemplates. The terminal adaptor sequences provide a universal site forprimer hybridization so that clonal expansion of the desired DNA targetscan be achieved and introduced into the automated sequencing processesused in NGS applications. The hybrid capture method is intended toreduce the complexity of the pool of random DNA fragments from, forexample, from 3×10⁹ bases (the human genome) to much smaller subsets of10⁴ to 10⁸ bases that are enriched for specific sequences of interest.The efficiency of this process directly relates to the quality ofcapture and enrichment achieved for desired DNA sequences from thestarting complex pool.

The NGS applications typically use the hybrid capture method ofenrichment in the following manner. A prepared pool of NGS templates isheat denatured and mixed with a pool of capture probe oligonucleotides(“baits”). The baits are designed to hybridize to the regions ofinterest within the target genome and are usually 60-200 bases in lengthand further are modified to contain a ligand that permits subsequentcapture of these probes. One common capture method incorporates a biotingroup (or groups) on the baits. After hybridization is complete to formthe DNA template:bait hybrids, capture is performed with a componenthaving affinity for only the bait. For example, streptavidin-magneticbeads can be used to bind the biotin moiety of biotinylated-baits thatare hybridized to the desired DNA targets from the pool of NGStemplates. Washing removes unbound nucleic acids, reducing thecomplexity of the retained material. The retained material is theneluted from the magnetic beads and introduced into automated sequencingprocesses.

Though DNA hybridization with the baits can be exquisitely specific,unwanted sequences remain in the enriched pool following completion ofthe hybrid capture method. The largest fraction of these unwantedsequences is present due to undesired hybridization events between NGStemplates having no complementarity to the baits and NGS templates thatdo. Two types of undesired hybridizations arising in the hybrid capturemethod include the following sequences: (1) highly repetitive DNAelements that are found in endogenous genomic DNA; and (2) the terminaladaptor sequences that are engineered into each of the NGS templates ofthe pool.

The repetitive endogenous DNA elements, such as an Alu sequence or LINEsequence, present in one DNA fragment in the complex pool can hybridizeto another similar element present in another unrelated DNA fragment.These fragments, which may originally derive from very differentlocations within the genome, become linked during the hybridizationprocess of the hybrid capture method. If one of these DNA fragmentsrepresents a desired fragment that contains a binding site for a bait,the unwanted fragment will be captured along with the desired fragment.This class of unwanted NGS templates can be reduced by adding an excessof the repeat elements to the hybridization reaction. Most commonly,human C_(o)t-1 DNA is added to the hybridization reaction, which bindsAlu, LINE, and other repeat sites in the target and blocks the abilityof NGS templates to interact with each other on that basis.

A more problematic class of unwanted NGS templates that are recoveredduring hybrid capture arises from interactions between terminal adaptorsequences that are engineered on each of the NGS templates of the pool.Because the pool of NGS templates typically will contain the identicalterminal adaptor sequences on every DNA fragment, the adaptor sequencesare present at a very high effective concentration(s) in thehybridization solution. Consequently, unrelated NGS templates can annealto each other through their termini, thereby resulting in a “daisychain” of otherwise unrelated DNA fragments being linked together. So ifone of these linked fragments contains a binding site for a bait, theentire daisy chain is captured. In this way, capture of a single desiredfragment can bring along a large number of undesired fragments, whichreduces the overall efficiency of enrichment for the desired fragment.This class of unwanted capture event can be reduced by adding an excessof single-stranded adaptor sequences to the hybridization reaction. Yetthe ability to effectively reduce the so-called daisy chain captureevents with an excess of adaptor sequences is limited to an efficiencyof about 50%-60% for capturing the desired fragment.

In spite of the use of C_(o)t-1 DNA and adaptor blockingoligonucleotides in the hybridization reaction, a significant amount ofcontaminating unwanted DNA fragments remain in the sequencing pool afterthe hybrid capture step, largely because the blocking methods are notcompletely successful. Thus, there is a need to improve captureefficiency and to reduce contamination from undesired sequences so thatone can devote resources to sequencing a greater fraction of targets ofinterest and fewer targets that are not of interest.

Thus, off-target nucleic acid interactions can limit the efficiency ofthe selection of target nucleic acids by hybridization (for example,solution hybridization) to a capture probe, for example, anoligonucleotide bait. Off-target selection can result, for example, inone or more of decreased yields of hybridization capture and/orartifactual hybrid capture, which in turn lead to inefficiencies insubsequent steps, for example, sequencing.

Off-target selection is typically increased when the stringencyconditions of hybrid selection are reduced, for example, when selectingfor a target:capture duplex having a lower nucleic acid meltingtemperature (for example, DNA:DNA duplexes as compared to RNA:DNAduplexes). Thus, capture of off-target sequence can be more of a problemin DNA:DNA hybridizations.

Typically, library members include a library insert, often a segment ofsequence from a gene of interest, for example, a segment for sequencing.If a member is on-target, the library insert forms a duplex with thecapture probe. Typically, library members also include and one or morenon-target sequences. These are typically not portions of a gene ofinterest but rather are adaptor sequences, amplification primers ortags, or bar code tags. The non-target sequence of the captureprobe-hybridized library member, can, by duplex formation with othersequences in the reaction mixture, lead to the selection of undesiredsequences, for example, off-target library members. While not wishing tobe bound by theory, concatenation between an on-target library memberand off-target sequences can result in selection of off-targetsequences.

Methods and compositions for minimizing selection of off-target nucleicacid, for example, minimizing the selection of library members that donot from a duplex with the capture probe are disclosed herein. Methodsand compositions are disclosed herein that reduce non-target sequence,for example, adaptor-mediated selection.

BRIEF SUMMARY OF THE INVENTION

In one aspect, the invention relates to an oligonucleotide for use in aselection method of a desired template nucleic acid, comprising anoligonucleotide having at least one T_(m)-enhancing group. In firstrespect, the oligonucleotide is useful in selection methods such as thehybrid capture method. In second respect, the oligonucleotide includesas desired template nucleic acid at least one member selected from apopulation of templates. In a third respect, the oligonucleotide issubstantially complementary to at least one sequence of the desiredtemplate. In a fourth respect, the oligonucleotide includes at least onemember selected from a blocker or a bait. In a fifth respect, theoligonucleotide includes as the at least one T_(m)-enhancing group atleast one member selected from the group consisting of a locked nucleicacid group, a bicyclic nucleic acid group, a C5-modified pyrimidine, apeptide nucleic acid group and combinations thereof. In the sixthrespect, the oligonucleotide includes as the at least oneT_(m)-enhancing group one of a locked nucleic acid group, a bicyclicnucleic acid group or a combination thereof. In a seventh respect, theoligonucleotide includes as the at least one T_(m)-enhancing group alocked nucleic acid group or a bicyclic nucleic acid group. As apreferred embodiment of the seventh respect, the oligonucleotide has asthe locked nucleic acid group or the bicyclic nucleic acid group anucleobase selected from the group consisting of cytosine, adenine andthymine, including mixtures of cytosine and adenine and mixtures ofcytosine and thymine. In a ninth respect, the oligonucleotide includesas the at least one T_(m)-enhancing group one that provides an optimalenhanced T_(m) value in the range comprising from about 1.4° C. to about25° C. In a tenth respect, the oligonucleotide includes at least onemember selected from the group consisting of SEQ ID NOS: 2, 3, 4, 5, 6,7, 8, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 24, 25, 27, 28, 30,32, 34 and 36. In an eleventh respect, oligonucleotide includes ablocker. In a preferred embodiment of these respects, the blocker hassubstantial sequence complementarity to at least one sequence at aterminus of the desired template nucleic acid. In a further elaborationof this preferred embodiment, the blocker includes a barcode domainhaving a plurality of nucleotides. In a further embodiment of thisrespect, the plurality of nucleotides includes from about 5 to about 12nucleotides arranged substantially contiguous. In another embodiment,the barcode domain comprises nucleotides having as nucleobases at leastone member selected from the group selected from adenine, thymine,cytosine, guanine, inosine, 3-nitropyrrole, 5-nitroindole, andcombinations thereof. In a twelfth respect, the oligonucleotide providesan improvement in the selection method of a desired template nucleicacid. In a preferred embodiment of this respect, the improvementconsists of an improved enrichment of the desire template nucleic acidrelative to undesired template nucleic acids. In yet another embodiment,the improved enrichment comprises of an enrichment of at least 65%. Inthe thirteenth respect, the oligonucleotide further includes a3′-terminal modification. In this respect, preferred embodiments of the3′-terminal modification prevents polymerase directed synthesis from theoligonucleotide. In another respect, the 3′-terminal modificationincludes a 2′,3′-dideoxynucleotide, a 3′-spacer C3 group, among others.

In a second aspect, the invention relates to a method of selecting adesired template nucleic acid from a population of template nucleicacids. The method includes two steps. The first step is contacting thepopulation of template nucleic acids with a first oligonucleotidecomprising a T_(m)-enhanced oligonucleotide to form a mixture. Thesecond step includes isolating the desired template nucleic acid fromthe mixture. In a first respect, the method provides as part of thecontacting step the sub-step of incubating the mixture at a temperatureof about optimal enhanced T_(m) value of the T_(m)-enhancedoligonucleotide. In a first preferred embodiment of this respect, theT_(m)-enhanced oligonucleotide includes a plurality of

T_(m)-enhancing groups. In this regard, the plurality of T_(m)-enhancinggroups comprises from about 2 to about 25 T_(m)-enhancing groups.Further embodiments provide that the plurality of T_(m)-enhancing groupscomprises locked nucleic acid groups or a bicyclic nucleic acid groups.Preferred aspects of these embodiments include features of the lockednucleic acid groups or the bicyclic nucleic acid groups havingnucleobases selected from the group consisting of cytosine, adenine andthymine. In a second respect, the method includes as the T_(m)-enhancedoligonucleotide at least one member selected from the group consistingof SEQ ID NOS: 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 18, 19,21, 22, 24, 25, 27, 28, 30, 32, 34 and 36. In a third respect, methodprovides the T_(m)-enhanced oligonucleotide that includes a blocker. Ina first preferred embodiment of this respect, the blocker hassubstantial sequence complementarity to at least one sequence at aterminus of each member of the population of template nucleic acids. Inyet another preferred embodiment, the blocker further includes a barcodedomain having a plurality of nucleotides. In some embodiments, theplurality of nucleotides includes from about 5 to about 12 nucleotidesarranged substantially contiguous. In other embodiments, the barcodedomain includes nucleotides having as nucleobases at least one memberselected from the group selected from adenine, thymine, cytosine,guanine, inosine, 3-nitropyrrole, 5-nitroindole, and combinationsthereof. In a third respect, the method has as the contacting step theobjective of resulting in substantial inhibition of complex formationbetween the desired template nucleic acid and undesired template nucleicacids. In a fourth respect, the method includes as the step of isolatingthe desired template nucleic acid two additional steps. The first stepis forming a hybrid complex between the desired nucleic acid and asecond oligonucleotide. The second step is separating the hybrid complexfrom the mixture. With regard to this fourth respect, the secondoligonucleotide includes a bait. In certain embodiments, the baitcomprises a sequence having substantial sequence complementarity to asequence within the desired template nucleic acid. In other embodiments,the bait comprises a plurality of T_(m)-enhancing groups. In yet otherembodiments, the bait includes a covalent modification to enableselection of the hybrid complex. As part of these latter embodiments,the covalent modification is a biotinylated group. Yet other embodimentsprovide for the hybrid complex being contacted with a solid supportimmobilized with avidin or streptavidin.

In a third aspect, the invention relates to a method of performingmassively parallel sequencing. The method includes four steps. The firststep is preparing a library population of template nucleic acids. Thesecond step is contacting the library population of template nucleicacids with at least one T_(m)-enhanced oligonucleotide as a blocker, aplurality of oligonucleotides as baits and C_(o)t-1 DNA to form amixture. The third step is isolating a plurality of desired templatenucleic acids from the mixture. The fourth step is sequencing theplurality of desired template nucleic acids. The at least one member ofthe plurality of oligonucleotides as baits has substantialcomplementarity to a sequence within at least one member of theplurality of desired template nucleic acids. In a first respect, themethod includes members of the library population of template nucleicacids each includes at least one identical terminal adaptor sequencehaving a size range from about 15 nucleotides to about 75 nucleotides.In a second respect, the method includes a blocker having substantialsequence complementarity to the at least one identical terminal adaptorsequence of the library population of template nucleic acids. In a thirdrespect, the method includes as the at least one identical terminaladaptor sequence a barcode domain. In a fourth respect, the methodprovides a blocker having substantial sequence complementarity to the atleast one identical terminal adaptor sequence. In a fifth respect,method includes as the contacting step the step of incubating themixture at a temperature of about optimal enhanced T_(m) value of the atleast one T_(m)-enhanced oligonucleotide. In a sixth respect, the methodprovides that the at least one T_(m)-enhanced oligonucleotide as ablocker includes at least one member selected from the group consistingof SEQ ID NOS: 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 18, 19,21, 22, 24, 25, 27, 28, 30, 32, 34 and 36. In a seventh respect, methodprovides that the step of isolating a plurality of desired templatenucleic acids from the mixture includes two steps. The first step isforming a plurality of hybrid complexes between the plurality of desiredtemplate nucleic acids and plurality of oligonucleotides as baits. Thesecond step is separating the plurality of hybrid complexes from themixture. In an eighth respect, the method provides as the plurality ofoligonucleotides as baits includes a plurality of T_(m)-enhancinggroups. In an embodiment of this respect, each bait includes a covalentmodification to enable selection of the hybrid complex that includes thebait. In a further embodiment of this respect, the covalent modificationis a biotinylated group. As another embodiment of this respect, theplurality of hybrid complexes is contacted with a solid supportimmobilized with avidin or streptavidin.

In another aspect, the invention features, a method of selecting nucleicacids or of reducing off-target nucleic acid selection in hybridizationreactions. The hybridization reaction can be a solid phase or solutionphase hybridization. The method can be used in the selection of librarymembers for subsequent processing, for example, for sequencing.

The method comprises:

(a) optionally, acquiring a library comprising a plurality of targetmembers, for example, target nucleic acid (for example, DNA or RNA)members, wherein one or more of the target members comprise an insertsequence (for example, a segment of a gene of interest) and a non-targetnucleic acid sequence (for example, an adaptor sequence); and

(b) contacting the library with a capture probe, for example, a bait setor a plurality of bait sets, and a blocking oligonucleotide, wherein,

(i) a blocking oligonucleotide is complementary to, or can form a duplexwith, the non-target nucleic acid sequence of the library member (forexample, an adaptor sequence), and

(ii) the value for a parameter related to the binding interactionbetween the blocking oligonucleotide and a non-target nucleic acidsequence of the library member is higher than the value for thenon-target nucleic acid sequence to a background nucleic acid, forexample, other complementary non-target nucleic acid sequences,

thereby minimizing off-target selection.

In an embodiment the method further comprising providing selectedlibrary members (sometimes referred to herein as “library catch”).

In an embodiment, the method further comprises separating the selectedlibrary members from the capture probe.

In an embodiment, the method further comprises sequencing the insert ofa selected library member, for example, sequencing the inserts fromleast 2, 5, 10, 15, 20, 30, or 50, genes or nucleic acid alterations,for example, genes or nucleic acid alterations described herein.

In an embodiment, the value for a parameter related to bindinginteraction can be a value for affinity, association rate, the inverseof dissociation rate, or nucleic acid melting temperature (for example,T_(m), the temperature at which half of the DNA strands are in thedouble-helical state and half are in the random coil state).

In an embodiment, the method comprises the use of a first blockingoligonucleotide which forms a duplex with a first non-target nucleicacid sequence, for example, a first adaptor sequence, and, optionally, asecond blocking oligonucleotide which forms a duplex with a secondnon-target nucleic acid sequence, for example, a second adaptorsequence. A set of oligonucleotide blockers comprises a plurality ofdifferent oligonucleotide blockers.

In an embodiment the blocking oligonucleotide inhibits the formation ofa duplex between a sequence in the reaction and the non-target sequenceof a library member that is duplexed to the capture probe (for example,the blocking oligonucleotide inhibits formation of concatenated chainsof library members).

In an embodiment, a library member comprises an insert, for example, asubgenomic interval, and a non-target sequence, for example, a sequencecommon to a plurality of library members. In an embodiment, the insertsare subgenomic sequences, for example, from nucleic acid from a tumorsample, and the non-target sequence is non-genomically occurringsequence or a sequence not present in the subgenomic sequences, forexample, an amplification tag or bar coding tag.

In an embodiment, the library members, or selected library members,include subgenomic intervals from at least 2, 5, 10, 15, 20, 30, or 50,genes or nucleic acid alterations, for example, genes or nucleic acidalterations described herein.

In an embodiment, a plurality of library members, or selected librarymembers, for example, at X (wherein X is equal to 2, 5, 10, 20, 50, 100,or 200) library members, or selected library members, have a firstnon-target sequence at the 5′ end of the insert and a second non-targetsequence at the 3′ end of the insert.

In an embodiment the non-target sequence includes a non-target sequencethat is present in a plurality of non-target sequences, for example, asequence for amplification, and a non-target sequence that is unique,for example, a barcode. Typically some, most substantially all or all ofthe members of the library will include a common non-target sequence. Inembodiments the library, or the selected library members, comprises atleast X members, (wherein X is equal to 1, 2, 5, 10, 20, 50, 100, or200) having a common non-target sequence.

In one embodiment, the blocking oligonucleotide forms a duplex with anon-target nucleic acid sequence of at least X library members (whereinX is equal to 1, 2, 5, 10, 20, 50, 100, or 200), which duplex has aT_(m) that is higher than the T_(m) of a duplex formed by a non-targetnucleic acid sequence to a background nucleic acid, for example, thecomplement of the non-target sequence. In one embodiment, the highernucleic acid melting temperature of the blocking oligonucleotide duplexis from about 5° C. to 25° C., or greater (for example, 5° C., 10° C.,15° C., 20° C., 25° C., or greater). In one embodiment, the T_(m) forthe duplex between the blocking oligonucleotide and the non-targetnucleic acid sequence of the library member is higher than is the T_(m)for a duplex of the non-target nucleic acid sequence and its exactcomplement.

In other embodiments, the blocking oligonucleotide has an associationrate to a non-target nucleic acid sequence of at least X library members(wherein X is equal to 1, 2, 5, 10, 20, 50, 100, or 200), that is higherthan the association rate of the non-target nucleic acid sequence to abackground nucleic acid, for example, the complement of the non-targetsequence. In one embodiment, the higher association rate is about 2- togreater than 10-fold that of the non-target nucleic acid sequence to thebackground nucleic acid (for example, 2-, 4-, 6-, 8-, 10-fold, orgreater).

In yet other embodiments, the blocking oligonucleotide has adissociation rate to the non-target nucleic acid sequence of at least Xlibrary members (wherein X is equal to 1, 2, 5, 10, 20, 50, 100, or 200)that is lower than the dissociation rate of the non-target nucleic acidsequence to a background nucleic acid, for example, the complement ofthe non-target sequence. In one embodiment, the lower dissociation rateis about 2- to greater than 10-fold that of the non-target nucleic acidsequence to the background nucleic acid (for example, 2-, 4-, 6-, 8-,10-fold, or greater).

In one embodiment, the length of the blocking oligonucleotide results inan increase in the binding interaction of the blocking oligonucleotidefor the non-target nucleic acid sequence of the library member (forexample, the adaptor sequence), relative to the background nucleic acid.

In an embodiment, the duplex formed between the blocking oligonucleotideand non-target nucleic acid sequence of at least X library members(wherein X is equal to 1, 2, 5, 10, 20, 50, 100, or 200), is longer thanthe duplex formed between the non-target sequence and its complement,for example, between the Watson and Crick strands of a double-strandedadaptor. In embodiments, the duplex between a blocking oligonucleotideand non-target nucleic acid sequence is at least 1, 2, 3, 4, 5, 6, 7, 8,9, 10, 15, or 20 nucleotides longer than the duplex formed between thenon-target sequence and its complement, for example, between the Watsonand Crick strands of a double-stranded adaptor.

In an embodiment, the blocking oligo comprises one or morenon-naturally-occurring nucleotides. In embodiments a duplex formedbetween the blocking oligonucleotide having non-naturally-occurringnucleotides and the non-target nucleic acid sequence of at least Xlibrary members (wherein X is equal to 1, 2, 5, 10, 20, 50, 100, or200), has the value for a parameter related to the binding interaction(for example, affinity, association rate, inverse of dissociation rate,or T_(m)) that is higher than the value for the non-target nucleic acidsequence to a background nucleic acid, for example, other complementarynon-target nucleic acid sequences. Exemplary non-naturally occurringoligonucleotides include modified DNA or RNA nucleotides. Exemplarymodified nucleotides (for example, modified RNA or DNA nucleotides)include, but are not limited to, a locked nucleic acid (LNA), whereinthe ribose moiety of an LNA nucleotide is modified with an extra bridgeconnecting the 2′ oxygen and 4′ carbon; peptide nucleic acid (PNA), forexample, a PNA composed of repeating N-(2-aminoethyl)-glycine unitslinked by peptide bonds; a DNA or RNA oligonucleotide modified tocapture low GC regions; a bicyclic nucleic acid (BNA); a crosslinkedoligonucleotide; a modified 5-methyl deoxycytidine; and2,6-diaminopurine. Other modified DNA and RNA nucleotides are known inthe art.

In an embodiment, the blocking oligonucleotide is or comprises RNA andthe non-target nucleic acid sequence, for example, an adaptor, is orcomprises DNA. In an embodiment, the non-target nucleic acid sequence isa sequence common to a plurality of library members, for example, atleast X library members (wherein X is equal to 2, 5, 10, 20, 50, 100, or200), for example, a sequence that can be used for amplification, forexample, PCR, bridge PCR, amplification.

In an embodiment the non-target nucleic acid sequence is a sequence thatcan be used for amplification, for example, PCR, bridge PCR,amplification, and the background nucleic acid is a second non-targetsequence

In an embodiment, the capture probe is DNA (for example, as opposed toRNA). In embodiments, the capture probe includes one or more DNAoligonucleotides (for example, a naturally or non-naturally occurringDNA oligonucleotide.

In an embodiment, the capture probe is RNA. In embodiments, the captureprobe includes one or more RNA oligonucleotides (for example, anaturally or non-naturally occurring RNA oligonucleotide.

In embodiment a blocking oligonucleotide is 20-80, 30-80, 40-80, 50-80,70-80, 30-75, 30-65, 30-55, 30-45, 40-70, 40-60, 40-50, 50-60,50-70,60-70, nucleotides in length. In an embodiment, the library insert is50-200, 77-150, or 100-150 nucleotides in lengths as described elsewhereherein.

In another aspect, the invention features, a preparation, comprising aplurality of blocking oligonucleotides, for example, as describedherein. In an embodiment the preparation further comprises one or bothof: a plurality of library members, for example, as described herein;and a capture probe, for example, as described herein.

In another aspect, the invention features, a kit, comprising a pluralityof blocking oligonucleotides, for example, as described herein. In anembodiment the kit further comprises one or both of: a plurality oflibrary members, for example, as described herein; and a capture probe,for example, as described herein. In embodiments the components areprovided in separate containers, for example, the blockingoligonucleotide is provided in a container and another component, forexample, a buffer, or a plurality of library members, for example, asdescribed herein or a capture probe, for example, as described herein,is provided in a different container(s).

In another aspect, the invention features, a method of reducingoff-target nucleic acid selection described herein combined with anothermethod described herein, for example, a sequencing method describedherein, an alignment method described herein, a mutation calling methoddescribed herein, or a method that uses a bait described herein.

Off-target selection can also be minimized by the use of non-targetsequences that are sufficiently short that a duplex of non-targetsequences is less stable than is a duplex of the insert sequence of alibrary member and the capture probe. Thus, in another aspect, theinvention features a method of reducing off-target nucleic acidselection, for example, in solid phase or solution hybridization. Themethod can be used in the selection of library members for subsequentsequencing.

The method comprises:

(a) optionally, acquiring a library comprising a plurality of targetmembers, for example, target nucleic acid (for example, DNA or RNA)members, wherein one or more of the target members comprise an insertsequence (for example, a segment of a gene of interest) and a non-targetnucleic acid sequence (for example, an adaptor sequence); and

(b) contacting the library with a capture probe, for example, a bait setor a plurality of bait sets;

wherein, the non-target sequences are sufficiently short such that thevalue for a parameter related to the binding interaction between theinsert sequence and the capture probe is higher for than that value forthe non-target nucleic acid sequence and its complement, therebyminimizing off-target selection.

In an embodiment the method further comprising providing selectedlibrary members (sometimes referred to herein as “library catch”).

In an embodiment, the method further comprises separating the selectedlibrary members from the capture probe.

In an embodiment, the method further comprises sequencing the insert ofa selected library member, for example, sequencing the inserts fromleast 2, 5, 10, 15, 20, 30, or 50, genes or nucleic acid alterations,for example, genes or nucleic acid alterations described herein.

In an embodiment, the value for a parameter related to bindinginteraction can be a value for affinity, association rate, the inverseof dissociation rate, or nucleic acid melting temperature (for example,T_(m), the temperature at which half of the DNA strands are in thedouble-helical state and half are in the random coil state).

In an embodiment, a library member comprises an insert, for example, asubgenomic interval, and a non-target sequence, for example, a sequencecommon to a plurality of library members. In an embodiment, the insertsare subgenomic sequences, for example, from nucleic acid from a tumorsample, and the non-target sequence is non-naturally occurring sequenceor a sequence not present in the subgenomic sequences, for example, aamplification tag or bar coding tag.

In an embodiment, the library members, or selected library members,include subgenomic intervals from at least 2, 5, 10, 15, 20, 30, or 50,genes or nucleic acid alterations, for example, genes or nucleic acidalterations described herein.

In an embodiment, a plurality of library members, or selected librarymembers, for example, at X (wherein X is equal to 2, 5, 10, 20, 50, 100,or 200) library members, or selected library members, have a firstnon-target sequence at the 5′ end of the insert and a second non-targetsequence at the 3′ end of the insert.

In an embodiment the non-target sequence includes a non-target sequencethat is present in a plurality of non-target sequences, for example, asequence for amplification, and a non-target sequence that is unique,for example, a barcode. Typically some, most substantially all or all ofthe members of the library will include a common non-target sequence. Inembodiments the library, or the selected library members, comprises atleast X members, (wherein X is equal to 1, 2, 5, 10, 20, 50, 100, or200) having a common non-target sequence.

In one embodiment, the insert sequence forms a duplex with the captureprobe for at least X library members (wherein X is equal to 1, 2, 5, 10,20, 50, 100, or 200), which duplex has a T_(m) that is higher than theT_(m) of a duplex formed by a non-target nucleic acid sequence to abackground nucleic acid, for example, the complement of the non-targetsequence. In one embodiment, the higher nucleic acid melting temperatureof the insert sequence/capture probe duplex is from about 5° C. to 25°C., or greater (for example, 5° C., 10° C., 15° C., 20° C., 25° C., orgreater). In one embodiment, the T_(m) for the duplex between the insertsequence/capture probe is higher than is the T_(m) for a duplex of thenon-target nucleic acid sequence and its exact complement.

In other embodiments, the insert sequence has an association rate to theprobe for at least X library members (wherein X is equal to 1, 2, 5, 10,20, 50, 100, or 200), that is higher than the association rate of thenon-target nucleic acid sequence to a background nucleic acid, forexample, the complement of the non-target sequence. In one embodiment,the higher association rate is about 2- to greater than 10-fold that ofthe non-target nucleic acid sequence to the background nucleic acid (forexample, 2-, 4-, 6-, 8-, 10-fold, or greater).

In yet other embodiments, the insert sequence has a dissociation rate tofor the capture probe for at least X library members (wherein X is equalto 1, 2, 5, 10, 20, 50, 100, or 200) that is lower than the dissociationrate of the non-target nucleic acid sequence to a background nucleicacid, for example, the complement of the non-target sequence. In oneembodiment, the lower dissociation rate is about 2- to greater than10-fold that of the non-target nucleic acid sequence to the backgroundnucleic acid (for example, 2-, 4-, 6-, 8-, 10-fold, or greater).

In an embodiment the non-target nucleic acid sequence is a sequence thatcan be used for amplification, for example, PCR, bridge PCR,amplification, and the background nucleic acid is a second non-targetsequence

In an embodiment, the capture probe is DNA (for example, as opposed toRNA). In an embodiment, the capture probe is RNA.

In an embodiment, the library insert is 50-200, 77-150, or 100-150nucleotides in lengths as described elsewhere herein.

In an embodiment the method further comprises the use of a blockingoligonucleotide, as described herein.

Additional features and embodiments of the invention are describedherein.

In one embodiment, the method further comprises:

(c) acquiring a read for a subgenomic interval from a tumor member fromsaid library or library catch, for example, by sequencing, for example,with a next generation sequencing method;

(d) aligning said read; and

(e) assigning a nucleotide value (for example, calling a mutation, forexample, with a Bayesian method) from said read for a preselectednucleotide position, for example, for a preselected nucleotide positionin each of a plurality of subgenomic intervals, for example, each of aplurality genes,

thereby analyzing said sample.

In an embodiment:

(i) each of X nucleotide positions is analyzed under a unique set ofconditions for one or a combination of steps (b), (c), (d), or (e)(wherein unique means different from the other X-1 sets of conditionsand wherein X is at least 2, 5, 10, 20, 30, 40, 50, 100, 200, 300 or500). For example, a first set of conditions, for example, a set ofconditions described herein, is used for a first nucleotide position,for example, in a first subgenomic interval or gene, and a second set ofconditions, for example, a second set of conditions described herein, isused for a second nucleotide position, for example, in a secondsubgenomic interval or gene;

(ii) for each of X nucleotide positions, responsive to a characteristic,for example, a characteristic described herein, of a preselectedalteration, for example, mutation, that can occur at the nucleotideposition, the nucleotide position is analyzed under a unique set ofconditions (wherein unique means different from the other X-1 sets ofconditions and wherein X is at least 2, 5, 10, 20, 30, 40, 50, 100, 200,300 or 500). For example, responsive to a characteristic, for example, acharacteristic described herein, of a preselected alteration, forexample, mutation, that can occur at a nucleotide position in a firstsubgenomic interval, the nucleotide position is analyzed under a firstset of conditions, and responsive to a characteristic, for example, acharacteristic described herein, of a preselected alteration, forexample, mutation, that can occur at a nucleotide position in a secondsubgenomic interval, the nucleotide position is analyzed under secondset of conditions;

(iii) wherein said method is performed on a sample, for example, apreserved tumor sample, under conditions that allow for 95, 98, or 99%sensitivity or specificity for nucleotide positions in at least 2, 5,10, 20, 50 or 100 subgenomic intervals, for example, genes; or

(iv) wherein the method comprises one or more or all of:

a) sequencing a first subgenomic interval to provide for about 500× orhigher sequencing depth, for example, to sequence a mutation present inno more than 5% of the cells from the sample;

b) sequencing a second subgenomic interval to provide for about 200× orhigher, for example, about 200×-about 500×, sequencing depth, forexample, to sequence a mutation present in no more than 10% of the cellsfrom the sample;

c) sequencing a third subgenomic interval to provide for about 10-100×sequencing depth, for example, to sequence one or more subgenomicintervals (for example, exons) that are chosen from: a) apharmacogenomic (PGx) single nucleotide polymorphism (SNP) that mayexplain the ability of patient to metabolize different drugs, or b) agenomic SNPs that may be used to uniquely identify (for example,fingerprint) a patient;

d) sequencing a fourth subgenomic interval to provide for about 5-50×sequencing depth, for example, to detect a structural breakpoint, suchas a genomic translocation or an indel. For example, detection of anintronic breakpoint requires 5-50× sequence-pair spanning depth toensure high detection reliability. Such bait sets can be used to detect,for example, translocation/indel-prone cancer genes; or

-   -   e) sequencing a fifth subgenomic interval to provide for about        0.1-300× sequencing depth, for example, to detect copy number        changes. In one embodiment, the sequencing depth ranges from        about 0.1-10× sequencing depth to detect copy number changes. In        other embodiments, the sequencing depth ranges from about        100-300× to detect a genomic SNPs/loci that is used to assess        copy number gains/losses of genomic DNA or        loss-of-heterozygosity (LOH).

Exemplary first and second sets of conditions include those wherein:

a first bait set is used for the first subgenomic interval and a secondbait set is used for the second subgenomic interval;

a first alignment method is applied to a read for the first subgenomicinterval and a second alignment method is applied to a read for secondsubgenomic interval;

a first mutation calling method is applied to a nucleotide position ofthe first subgenomic interval and a second mutation calling method isapplied to a nucleotide position of the second subgenomic interval.

In an embodiment:

a first nucleotide position is analyzed with a first set of baitconditions, a first alignment method, and a first mutation callingmethod;

a second nucleotide position is analyzed with said first set of baitconditions, a second alignment method, and said first mutation callingmethod;

a third nucleotide position is analyzed with said first set of baitconditions, said first alignment method, and a second mutation callingmethod, to provide three nucleotide positions each analyzed underunique, as compared to the other two, conditions.

In an embodiment, the conditions comprise those wherein:

a first bait set is used for the first subgenomic interval and a secondbait set is used for the second subgenomic interval;

a first alignment method is applied to a read for the first subgenomicinterval and a second alignment method is applied to a read for secondsubgenomic interval; or a first mutation calling method is applied to anucleotide position of the first subgenomic interval and a secondmutation calling method is applied to a nucleotide position of thesecond subgenomic interval.

Exemplary characteristics include:

(i) the gene, or type of gene, in which the alteration is located, forexample, an oncogene or tumor suppressor, a gene or type of genecharacterized by a preselected or variant or type of variant, forexample, a mutation, or by a mutation of a preselected frequency, orother gene or type of gene described herein;

(ii) the type of alteration, for example, a substitution, insertion,deletion, or translocation;

(iii) the type of sample, for example, an FFPE sample, being analyzedfor the alteration;

(iv) sequence in or near said the nucleotide position of the alterationbeing evaluated, for example, sequence which can affect the expectedpropensity for misalignment for the subgenomic interval, for example,the presence of repeated sequences in or near the nucleotide position;

(v) a prior (for example, literature) expectation of observing a readshowing the alteration, for example, mutation, for example, in a tumorof preselected type;

(vi) the probability of observing a read showing the alteration due tobase-calling error alone); or

(vii) a preselected depth of sequencing desired for detecting thealteration.

In an embodiment, the characteristic is other than the identity of thenucleotide being sequenced, that is, the characteristic is not whetherthe sequence is a or t.

In an embodiment, subgenomic intervals from at least X genes, forexample, at least X genes from Tables 1 and 1A, for example, geneshaving the priority 1 annotation in Table 1 and 1A, are analyzed underdifferent conditions, and X is equal to 2, 3, 4, 5, 10, 15, 20, or 30.

In an embodiment, the method comprises one or more of the following:

(i) the method, for example, (b) of the method above, comprises the useof a bait set described herein;

(ii) the method, for example, (c) of the method above, comprisesacquiring reads for a set or group of subgenomic intervals or from a setor group of genes described herein;

(iii) the method, for example, (d) of the method above, comprises theuse of a plurality of alignment methods described herein;

(iv) the method, for example, (e) of the method above, comprises the useof a plurality of methods for assigning a nucleotide value to apreselected nucleotide position, described herein;”

or

(v) the method comprises assigning a nucleotide value to a set ofsubgenomic intervals described herein.

In an embodiment, the method includes: (i) and one, two, three, or allof (ii)-(v). In an embodiment, the method includes: (ii) and one, two,three, or all of (i) and (iii)-(v). In an embodiment, the methodincludes: (iii) and one, two, three, or all of (i), (ii), (iv) and (v).In an embodiment, the method includes: (iv) and one, two, three, or allof (i)-(iii) and (v). In an embodiment, the method includes: (v) andone, two, three, or all of (i)-(iv).

Baits

Methods described herein provide for selection and/or sequencing of alarge number of genes and gene products from samples, for example, tumorsamples, from one or more subjects by the appropriate selection ofbaits, for example, baits for use in solution hybridization, for theselection of target nucleic acids to be sequenced. The efficiency ofselection for various subgenomic intervals, or classes thereof, arematched according to bait sets having preselected efficiency ofselection. As used in this section, “efficiency of selection” refers tothe level or depth of sequence coverage as it is adjusted according to atarget subgenomic interval(s).

Thus, a method (for example, element (b) of the method recited above)comprises contacting the library with a plurality of baits to provideselected members (for example, a library catch). In certain embodiments,the method comprises contacting the library with a plurality, forexample, at least two, three, four, or five, of baits or bait sets,wherein each bait or bait set of said plurality has a unique (as opposedto the other bait sets in the plurality), preselected efficiency forselection. For example, each unique bait or bait set provides for aunique depth of sequencing. The term “bait set”, as used herein,collectively refers to one bait or a plurality of bait molecules.

In an embodiment, the efficiency of selection of a first bait set in theplurality differs from the efficiency of a second bait set in theplurality by at least 2 fold. In an embodiment, the first and secondbait sets provide for a depth of sequencing that differs by at least 2fold.

In another embodiment, the method comprises contacting one, or aplurality of the following bait sets with the library:

a) a bait set that selects sufficient members comprising a subgenomicinterval to provide for about 500× or higher sequencing depth, forexample, to sequence a mutation present in no more than 5% of the cellsfrom the sample;

b) a bait set that selects sufficient members comprising a subgenomicinterval to provide for about 200× or higher, for example, about200×-about 500×, sequencing depth, for example, to sequence a mutationpresent in no more than 10% of the cells from the sample;

c) a bait set that selects sufficient members comprising a subgenomicinterval to provide for about 10-100× sequencing depth, for example, tosequence one or more subgenomic intervals (for example, exons) that arechosen from: a) a pharmacogenomic (PGx) single nucleotide polymorphism(SNP) that may explain the ability of patient to metabolize differentdrugs, or b) a genomic SNPs that may be used to uniquely identify (forexample, fingerprint) a patient;

d) a bait set that selects sufficient members comprising a subgenomicinterval to provide for about 5-50× sequencing depth, for example, todetect a structural breakpoint, such as a genomic translocation or anindel. For example, detection of an intronic breakpoint requires 5-50×sequence-pair spanning depth to ensure high detection reliability. Suchbait sets can be used to detect, for example, translocation/indel-pronecancer genes; or

-   -   e) a bait set that selects sufficient members comprising a        subgenomic interval to provide for about 0.1-300× sequencing        depth, for example, to detect copy number changes.

In one embodiment, the sequencing depth ranges from about 0.1-10×sequencing depth to detect copy number changes. In other embodiments,the sequencing depth ranges from about 100-300× to detect a genomicSNPs/loci that is used to assess copy number gains/losses of genomic DNAor loss-of-heterozygosity (LOH). Such bait sets can be used to detect,for example, amplification/deletion-prone cancer genes. The level ofsequencing depth as used herein (for example, X-fold level of sequencingdepth) refers to the level of coverage of reads (for example, uniquereads), after detection and removal of duplicate reads, for example, PCRduplicate reads.

In one embodiment, the bait set selects a subgenomic interval containingone or more rearrangements, for example, an intron containing a genomicrearrangement. In such embodiments, the bait set is designed such thatrepetitive sequences are masked to increase the selection efficiency. Inthose embodiments where the rearrangement has a known juncture sequence,complementary bait sets can be designed to the juncture sequence toincrease the selection efficiency.

In embodiments, the method comprises the use of baits designed tocapture two or more different target categories, each category having adifferent bait design strategies. In embodiments, the hybrid capturemethods and compositions disclosed herein capture a defined subset oftarget sequences (for example, target members) and provide homogenouscoverage of the target sequence, while minimizing coverage outside ofthat subset. In one embodiment, the target sequences include the entireexome out of genomic DNA, or a selected subset thereof. The methods andcompositions disclosed herein provide different bait sets for achievingdifferent depths and patterns of coverage for complex target nucleicacid sequences (for example, nucleic acid libraries).

In an embodiment, the method comprises providing selected members of anucleic acid library (for example, a library catch). The methodincludes:

providing a library (for example, a nucleic acid library) comprising aplurality of members, for example, target nucleic acid members (forexample, including a plurality of tumor members, reference members,and/or PGx members);

contacting the library, for example, in a solution-based reaction, witha plurality of baits (for example, oligonucleotide baits) to form ahybridization mixture comprising a plurality of bait/member hybrids;

separating the plurality of bait/member hybrids from said hybridizationmixture, for example, by contacting said hybridization mixture with abinding entity that allows for separation of said plurality ofbait/member hybrid, thereby providing a library-catch (for example, aselected or enriched subgroup of nucleic acid molecules from thelibrary),

wherein the plurality of baits includes two or more of the following:

a) a first bait set that selects a high-level target (for example, oneor more tumor members that include a subgenomic interval, such a gene,an exon, or a base) for which the deepest coverage is required to enablea high level of sensitivity for an alteration (for example, one or moremutations) that appears at a low frequency, for example, about 5% orless (that is, 5% of the cells from the sample harbor the alteration intheir genome). In one embodiment; the first bait set selects (forexample, is complementary to) a tumor member that includes an alteration(for example, a point mutation) that requires about 500× or highersequencing depth;

b) a second bait set that selects a mid-level target (for example, oneor more tumor members that include a subgenomic interval, such as agene, an exon, or a base) for which high coverage is required to enablehigh level of sensitivity for an alteration (for example, one or moremutations) that appears at a higher frequency than the high-level targetin a), for example, a frequency of about 10% (that is, 10% of the cellsfrom the sample harbor the alteration in their genome). In oneembodiment; the second bait set selects (for example, is complementaryto) a tumor member that includes an alteration (for example, a pointmutation) that requires about 200× or higher sequencing depth;

c) a third bait set that selects a low-level target (for example, one ormore PGx members that includes a subgenomic interval, such as a gene, anexon, or a base) for which low-medium coverage is required to enablehigh level of sensitivity, for example, to detect heterozygous alleles.For example, detection of heterozygous alleles requires 10-100×sequencing depth to ensure high detection reliability. In oneembodiment, third bait set selects one or more subgenomic intervals (forexample, exons) that are chosen from: a) a pharmacogenomic (PGx) singlenucleotide polymorphism (SNP) that may explain the ability of patient tometabolize different drugs, or b) a genomic SNPs that may be used touniquely identify (for example, fingerprint) a patient;

d) a fourth bait set that selects a first intron target (for example, amember that includes an intron sequence) for which low-medium coverageis required, for example, to detect a structural breakpoint, such as agenomic translocation or an indel. For example, detection of an intronicbreakpoint requires 5-50× sequence-pair spanning depth to ensure highdetection reliability. Said fourth bait sets can be used to detect, forexample, translocation/indel-prone cancer genes; or

e) a fifth bait set that selects a second intron target (for example, anintron member) for which sparse coverage is required to improve theability to detect copy number changes. For example, detection of aone-copy deletion of several terminal exons requires 0.1-300× coverageto ensure high detection reliability. In one embodiment, the coveragedepth ranges from about 0.1-10× to detect copy number changes. In otherembodiments, the coverage depth ranges from about 100-300× to detect agenomic SNPs/loci that is used to assess copy number gains/losses ofgenomic DNA or loss-of-heterozygosity (LOH). Said fifth bait sets can beused to detect, for example, amplification/deletion-prone cancer genes.

Any combination of two, three, four or more of the aforesaid bait setscan be used, for example, a combination of the first and the second baitsets; first and third bait sets; first and fourth bait sets; first andfifth bait sets; second and third bait sets; second and fourth baitsets; second and fifth bait sets; third and fourth bait sets; third andfifth bait sets; fourth and fifth bait sets; first, second and thirdbait sets; first, second and fourth bait sets; first, second and fifthbait sets; first, second, third, fourth bait sets; first, second, third,fourth and fifth bait sets, and so on.

In one embodiment, each of the first, second, third, fourth, or fifthbait set has a preselected efficiency for selection (for example,capture). In one embodiment, the value for efficiency of selection isthe same for at least two, three, four of all five baits according toa)-e). In other embodiments, the value for efficiency of selection isdifferent for at least two, three, four of all five baits according toa)-e). In some embodiments, at least two, three, four, or all five baitsets have a preselected efficiency value that differ.

For example, a value for efficiency of selection chosen from one of moreof:

(i) the first preselected efficiency has a value for first efficiency ofselection that is at least about 500× or higher sequencing depth (forexample, has a value for efficiency of selection that is greater thanthe second, third, fourth or fifth preselected efficiency of selection(for example, about 2-3 fold greater than the value for the secondefficiency of selection; about 5-6 fold greater than the value for thethird efficiency of selection; about 10 fold greater than the value forthe fourth efficiency of selection; about 50 to 5000-fold greater thanthe value for the fifth efficiency of selection);

(ii) the second preselected efficiency has a value for second efficiencyof selection that is at least about 200× or higher sequencing depth (forexample, has a value for efficiency of selection that is greater thanthe third, fourth or fifth preselected efficiency of selection (forexample, about 2 fold greater than the value for the third efficiency ofselection; about 4 fold greater than the value for the fourth efficiencyof selection; about 20 to 2000-fold greater than the value for the fifthefficiency of selection);

(iii) the third preselected efficiency has a value for third efficiencyof selection that is at least about 100× or higher sequencing depth (forexample, has a value for efficiency of selection that is greater thanthe fourth or fifth preselected efficiency of selection (for example,about 2 fold greater than the value for the fourth efficiency ofselection; about 10 to 1000-fold greater than the value for the fifthefficiency of selection);

(iv) the fourth preselected efficiency has a value for fourth efficiencyof selection that is at least about 50× or higher sequencing depth (forexample, has a value for efficiency of selection that is greater thanthe fifth preselected efficiency of selection (for example, about 50 to500-fold greater than the value for the fifth efficiency of selection);or

(v) the fifth preselected efficiency has a value for fifth efficiency ofselection that is at least about 10× to 0.1× sequencing depth.

In certain embodiments, the value for efficiency of selection ismodified by one or more of: differential representation of differentbait sets, differential overlap of bait subsets, differential baitparameters, mixing of different bait sets, and/or using different typesof bait sets.

For example, a variation in efficiency of selection (for example,relative sequence coverage of each bait set/target category) can beadjusted by altering one or more of:

(i) Differential representation of different bait sets—The bait setdesign to capture a given target (for example, a target member) can beincluded in more/fewer number of copies to enhance/reduce relativetarget coverage depths;

(ii) Differential overlap of bait subsets—The bait set design to capturea given target (for example, a target member) can include a longer orshorter overlap between neighboring baits to enhance/reduce relativetarget coverage depths;

(iii) Differential bait parameters—The bait set design to capture agiven target (for example, a target member) can include sequencemodifications/shorter length to reduce capture efficiency and lower therelative target coverage depths;

(iv) Mixing of different bait sets—Bait sets that are designed tocapture different target sets can be mixed at different molar ratios toenhance/reduce relative target coverage depths;

(v) Using different types of oligonucleotide bait sets—In certainembodiments, the bait set can include:

-   -   (a) one or more chemically (for example, non-enzymatically)        synthesized (for example, individually synthesized) baits,    -   (b) one or more baits synthesized in an array,    -   (c) one or more enzymatically prepared, for example, in vitro        transcribed, baits;    -   (d) any combination of (a), (b) and/or (c),    -   (e) one or more DNA oligonucleotides (for example, a naturally        or non-naturally occurring DNA oligonucleotide),    -   (f) one or more RNA oligonucleotides (for example, a naturally        or non-naturally occurring RNA oligonucleotide),    -   (g) a combination of (e) and (f), or    -   (h) a combination of any of the above.

The different oligonucleotide combinations can be mixed at differentratios, for example, a ratio chosen from 1:1, 1:2, 1:3, 1:4, 1:5, 1:10,1:20, 1:50; 1:100, 1:1000, or the like. In one embodiment, the ratio ofchemically-synthesized bait to array-generated bait is chosen from 1:5,1:10, or 1:20. The DNA or RNA oligonucleotides can be naturally- ornon-naturally-occurring. In certain embodiments, the baits include oneor more non-naturally-occurring nucleotide to, for example, increasemelting temperature. Exemplary non-naturally occurring oligonucleotidesinclude modified DNA or RNA nucleotides. Exemplary modified nucleotides(for example, modified RNA or DNA nucleotides) include, but are notlimited to, a locked nucleic acid (LNA), wherein the ribose moiety of anLNA nucleotide is modified with an extra bridge connecting the 2′ oxygenand 4′ carbon; peptide nucleic acid (PNA), for example, a PNA composedof repeating N-(2-aminoethyl)-glycine units linked by peptide bonds; aDNA or RNA oligonucleotide modified to capture low GC regions; abicyclic nucleic acid (BNA); a crosslinked oligonucleotide; a modified5-methyl deoxycytidine; and 2,6-diaminopurine. Other modified DNA andRNA nucleotides are known in the art.

In certain embodiments, a substantially uniform or homogeneous coverageof a target sequence (for example, a target member) is obtained. Forexample, within each bait set/target category, uniformity of coveragecan be optimized by modifying bait parameters, for example, by one ormore of:

(i) Increasing/decreasing bait representation or overlap can be used toenhance/reduce coverage of targets (for example, target members), whichare under/over-covered relative to other targets in the same category;

(ii) For low coverage, hard to capture target sequences (for example,high GC content sequences), expand the region being targeted with thebait sets to cover, for example, adjacent sequences (for example, lessGC-rich adjacent sequences);

(iii) Modifying a bait sequence can be made to reduce secondarystructure of the bait and enhance its efficiency of selection;

(iv) Modifying a bait length can be used to equalize meltinghybridization kinetics of different baits within the same category. Baitlength can be modified directly (by producing baits with varyinglengths) or indirectly (by producing baits of consistent length, andreplacing the bait ends with arbitrary sequence);

(v) Modifying baits of different orientation for the same target region(that is, forward and reverse strand) may have different bindingefficiencies. The bait set with either orientation providing optimalcoverage for each target may be selected;

(vi) Modifying the amount of a binding entity, for example, a capturetag (for example, biotin), present on each bait may affect its bindingefficiency. Increasing/decreasing the tag level of baits targeting aspecific target may be used to enhance/reduce the relative targetcoverage;

(vii) Modifying the type of nucleotide used for different baits can bealtered to affect binding affinity to the target, and enhance/reduce therelative target coverage; or

(viii) Using modified oligonucleotide baits, for example, having morestable base pairing, can be used to equalize melting hybridizationkinetics between areas of low or normal GC content relative to high GCcontent.

For example, different types of oligonucleotide bait sets can be used.In one embodiment, the value for efficiency of selection is modified byusing different types of bait oligonucleotides to encompass pre-selectedtarget regions. For example, a first bait set (for example, anarray-based bait set comprising 10,000-50,000 RNA or DNA baits) can beused to cover a large target area (for example, 1-2 MB total targetarea). The first bait set can be spiked with a second bait set (forexample, individually synthesized RNA or DNA bait set comprising lessthan 5,000 baits) to cover a pre-selected target region (for example,selected subgenomic intervals of interest spanning, for example, 250 kbor less, of a target area) and/or regions of higher secondary structure,for example, higher GC content. Selected subgenomic intervals ofinterest may correspond to one or more of the genes or gene productsdescribed herein, or a fragment thereof. The second bait set may includeabout 1-5,000, 2-5,000, 3-5,000, 10-5,000, 100-5,000, 500-5,000,100-5,000, 1000-5,000, 2,000-5,000 baits depending on the bait overlapdesired. In other embodiments, the second bait set can include selectedoligo baits (for example, less than 400, 200, 100, 50, 40, 30, 20, 10,5, 4, 3, 2 or 1 baits) spiked into the first bait set. The second baitset can be mixed at any ratio of individual oligo baits. For example,the second bait set can include individual baits present as a 1:1equimolar ratio. Alternatively, the second bait set can includeindividual baits present at different ratio (for example, 1:5, 1:10,1:20), for example, to optimize capture of certain targets (for example,certain targets can have a 5-10× of the second bait compared to othertargets).

In other embodiments, the efficiency of selection is adjusted byleveling the efficiency of individual baits within a group (for example,a first, second or third plurality of baits) by adjusting the relativeabundance of the baits, or the density of the binding entity (forexample, the hapten or affinity tag density) in reference todifferential sequence capture efficiency observed when using anequimolar mix of baits, and then introducing a differential excess ofinternally-leveled group 1 to the overall bait mix relative tointernally-leveled group 2.

In an embodiment, the method comprises the use of a plurality of baitsets that includes a bait set that selects a tumor member, for example,a nucleic acid molecule comprising a subgenomic interval from a tumorcell (also referred to herein as “a tumor bait set”). The tumor membercan be any nucleotide sequence present in a tumor cell, for example, amutated, a wild-type, a PGx, a reference or an intron nucleotidesequence, as described herein, that is present in a tumor or cancercell. In one embodiment, the tumor member includes an alteration (forexample, one or more mutations) that appears at a low frequency, forexample, about 5% or less of the cells from the tumor sample harbor thealteration in their genome. In other embodiments, the tumor memberincludes an alteration (for example, one or more mutations) that appearsat a frequency of about 10% of the cells from the tumor sample. In otherembodiments, the tumor member includes a subgenomic interval from a PGxgene or gene product, an intron sequence, for example, an intronsequence as described herein, a reference sequence that is present in atumor cell.

In another aspect, the invention features, a bait set described herein,combinations of individual bait sets described herein, for example,combinations described herein. The bait set(s) can be part of a kitwhich can optionally comprise instructions, standards, buffers orenzymes or other reagents.

Gene Selection

Preselected subgenomic intervals for analysis, for example, a group orset of subgenomic intervals for sets or groups of genes and otherregions, are described herein.

Thus, in embodiments, a method comprises selection and/or sequencing oflibrary members that include a subgenomic interval from at least five,six, seven, eight, nine, ten, fifteen, twenty, twenty-five, thirty ormore genes or gene products from the acquired nucleic acid sample,wherein the genes or gene products are chosen from: ABL1, AKT1, AKT2,AKT3, ALK, APC, AR, BRAF, CCND1, CDK4, CDKN2A, CEBPA, CTNNB1, EGFR,ERBB2, ESR1, FGFR1, FGFR2, FGFR3, FLT3, HRAS, JAK2, KIT, KRAS, MAP2K1,MAP2K2, MET, MLL, MYC, NF1, NOTCH1, NPM1, NRAS, NTRK3, PDGFRA, PIK3CA,PIK3CG, PIK3R1, PTCH1, PTCH2, PTEN, RB1, RET, SMO, STK11, SUFU, or TP53,thereby analyzing the tumor sample.

In other embodiments, the method comprises selection and/or sequencingof library members that include a subgenomic interval from at leastfive, six, seven, eight, nine, ten, fifteen, twenty, twenty-five, thirtyor more genes or gene products from the sample, wherein the genes orgene products are chosen from: ABL1, AKT1, AKT2, AKT3, ALK, APC, AR,BRAF, CCND1, CDK4, CDKN2A, CEBPA, CTNNB1, EGFR, ERBB2, ESR1, FGFR1,FGFR2, FGFR3, FLT3, HRAS, JAK2, KIT, KRAS, MAP2K1, MAP2K2, MET, MLL,MYC, NF1, NOTCH1, NPM1, NRAS, NTRK3, PDGFRA, PIK3CA, PIK3CG, PIK3R1,PTCH1, PTCH2, PTEN, RB1, RET, SMO, STK11, SUFU, or TP53.

In another embodiment, subgenomic intervals of one of the following setsor groups are analyzed. For example, subgenomic intervals associatedwith a tumor or cancer gene or gene product, a reference (for example, awild type) gene or gene product, and a PGx gene or gene product, canprovide a group or set of subgenomic intervals from the tumor sample.

In an embodiment, the method comprises selection and/or sequencing oflibrary members of a set of subgenomic intervals from the tumor sample,wherein the subgenomic intervals are chosen from at least 1, 2, 3, 4, 5,6, 7, 8, 9, 10, 11, 12, 13 or all of the following:

A) at least five, six, seven, eight, nine, ten, fifteen, twenty,twenty-five, thirty or more subgenomic intervals from a mutated orwild-type gene or gene product chosen from at least five or more of:ABL1, AKT1, AKT2, AKT3, ALK, APC, AR, BRAF, CCND1, CDK4, CDKN2A, CEBPA,CTNNB1, EGFR, ERBB2, ESR1, FGFR1, FGFR2, FGFR3, FLT3, HRAS, JAK2, KIT,KRAS, MAP2K1, MAP2K2, MET, MLL, MYC, NF1, NOTCH1, NPM1, NRAS, NTRK3,PDGFRA, PIK3CA, PIK3CG, PIK3R1, PTCH1, PTCH2, PTEN, RB1, RET, SMO,STK11, SUFU, or TP53;

B) at least five, six, seven, eight, nine, ten, fifteen, twenty,twenty-five, thirty, thirty-five, forty, forty-five, fifty, fifty-five,sixty, sixty-five, seventy, seventy-five, eighty, eighty-five, ninety,ninety-five, one hundred, one hundred and five, one hundred and ten, onehundred and fifteen, one hundred and twenty or more of subgenomicintervals from a mutated or wild type gene or gene product chosen fromat least five or more of: ABL2, ARAF, ARFRP1, ARID1A, ATM, ATR, AURKA,AURKB, BAP1, BCL2, BCL2A1, BCL2L1, BCL2L2, BCL6, BRCA1, BRCA2, CBL,CARD11, CBL, CCND2, CCND3, CCNE1, CD79A, CD79B, CDH1, CDH2, CDH20, CDH5,CDK6, CDK8, CDKN2B, CDKN2C, CHEK1, CHEK2, CRKL, CRLF2, DNMT3A, DOT1L,EPHA3, EPHA5, EPHA6, EPHA7, EPHB1, EPHB4, EPHB6, ERBB3, ERBB4, ERG,ETV1, ETV4, ETV5, ETV6, EWSR1, EZH2, FANCA, FBXW7, FGFR4, FLT1, FLT4,FOXP4, GATA1, GNA11, GNAQ, GNAS, GPR124, GUCY1A2, HOXA3, HSP9OAA1, IDH1,IDH2, IGF1R, IGF2R, IKBKE, IKZF1, INHBA, IRS2, JAK1, JAK3, JUN, KDM6A,KDR, LRP1B, LRP6, LTK, MAP2K4, MCL1, MDM2, MDM4, MEN1, MITF, MLH1, MPL,MRE11A, MSH2, MSH6, MTOR, MUTYH, MYCL1, MYCN, NF2, NKX2-1, NTRK1, NTRK2,PAK3, PAX5, PDGFRB, PKHD1, PLCG1, PRKDC, PTPN11, PTPRD, RAF1, RARA,RICTOR, RPTOR, RUNX1, SMAD2, SMAD3, SMAD4, SMARCA4, SMARCB1, SOX10,SOX2, SRC, TBX22, TET2, TGFBR2, TMPRSS2, TNFAIP3, TNK, TNKS2, TOP1,TSC1, TSC2, USP9X, VHL, or WT1;

C) at least five, six, seven, eight, nine, ten, fifteen, twenty, or moresubgenomic intervals from a gene or gene product according to Table 1,1A, 2, 3 or 4;

D) at least five, six, seven, eight, nine, ten, fifteen, twenty, or moresubgenomic intervals from a gene or gene product that is associated witha tumor or cancer (for example, is a positive or negative treatmentresponse predictor, is a positive or negative prognostic factor for, orenables differential diagnosis of a tumor or cancer, for example, a geneor gene product chosen from one or more of: ABL1, AKT1, ALK, AR, BRAF,BRCA1, BRCA2, CEBPA, EGFR, ERBB2, FLT3, JAK2, KIT, KRAS, MET, NPM1,PDGFRA, PIK3CA, RARA, AKT2, AKT3, MAP2K4, NOTCH1, and TP53;

E) at least five, six, seven, eight, nine, ten, or more subgenomicintervals including a mutated or a wild type codon chosen from one ormore of: codon 315 of the ABL 1 gene; codon 1114, 1338, 1450 or 1556 ofAPC; codon 600 of BRAF; codon 32, 33, 34, 37, 41 or 45 of CTNNB1; codon719, 746-750, 768, 790, 858 or 861 of EGFR; codon 835 of FLT3; codon 12,13, or 61 of HRAS; codon 617 of JAK2; codon 816 of KIT; codon 12, 13, or61 of KRAS; codon 88, 542, 545, 546, 1047, or 1049 of PIK3CA; codon 130,173, 233, or 267 of PTEN; codon 918 of RET; codon 175, 245, 248, 273, or306 of TP53 (for example, at least five, ten, fifteen, twenty or moresubgenomic intervals that include one or more of the codons shown inTable 1).

F) at least five, six, seven, eight, nine, ten, fifteen, twenty,twenty-five, thirty, or more of subgenomic intervals from a mutated orwild type gene or gene product (for example, single nucleotidepolymorphism (SNP)) of a subgenomic interval that is present in a geneor gene product associated with one or more of drug metabolism, drugresponsiveness, or toxicity (also referred to therein as “PGx” genes)chosen from: ABCB1, BCC2, ABCC4, ABCG2, Clorf144, CYP1B1, CYP2C19,CYP2C8, CYP2D6, CYP3A4, CYP3A5, DPYD, ERCC2, ESR2, FCGR3A, GSTP1, ITPA,LRP2, MAN1B1, MTHFR, NQO1, NRP2, SLC19A1, SLC22A2, SLCO1B3, SOD2,SULT1A1, TPMT, TYMS, UGT1A1, or UMPS;

G) at least five, six, seven, eight, nine, ten, fifteen, twenty,twenty-five, thirty, or more of subgenomic intervals from a mutated orwild type PGx gene or gene product (for example, single nucleotidepolymorphism (SNP)) of a subgenomic interval that is present in a geneor gene product associated with one or more of: (i) better survival of acancer patient treated with a drug (for example, better survival of abreast cancer patient treated with paclitaxel (for example, an ABCB 1gene)); (ii) paclitaxel metabolism (for example, CYP2C8 genes atdifferent loci and mutations shown in Table 2; CYP3A4 gene); (iii)toxicity to a drug (for example, 6-MP toxicity as seen with ABCC4 gene(Table 2); 5-FU toxicity as seen with DPYD gene, TYMS gene, or UMPS gene(Table 2); purine toxicity as seen with a TMPT gene (Table 2);daunorubicin toxicity as seen with NRP2 gene; Clorf144 gene, CYP1B1 gene(Table 2); or (iv) a side effect to a drug (for example, ABCG2, TYMS,UGT1A1, ESR1 and ESR2 genes (Table 2));

H) a translocation alteration of at least 5, 10, 15, 20, 25, 30, 35, 40,45, 50, 75, 110 or more genes or gene products according to Table 3;

I) a translocation alteration of at least 5, 10, 15, 20, 25, 30, 35, 40,45, 50, 75, 110 or more genes or gene products according to Table 3 in asolid tumor sample from the cancer types specified therein;

J) a translocation alteration of at least 5, 10, 15, 20, 25, 30, 35, 40,45, 50, 75, 100, 150, 200 or more genes or gene products according toTable 4;

K) a translocation alteration of at least 5, 10, 15, 20, 25, 30, 35, 40,45, 50, 75, 100, 150, 200 or more genes or gene products according toTable 4 in a heme tumor sample from the cancer types specified therein;

L) at least five genes or gene products selected from Table 1-4, whereinan allelic variation, for example, at the preselected position, isassociated with a preselected type of tumor and wherein said allelicvariation is present in less than 5% of the cells in said tumor type;

M) at least five genes or gene products selected from Table 1, 1A-4,which are embedded in a GC-rich region; or

N) at least five genes or gene products indicative of a genetic (forexample, a germline risk) factor for developing cancer (for example, thegene or gene product is chosen from one or more of BRCA1, BRCA2, EGFR,HRAS, KIT, MPL, ALK, PTEN, RET, APC, CDKN2A, MLH1, MSH2, MSH6, NF1, NF2,RB1, TP53, VHL or WT1).

In yet another embodiment, the method comprises selection and/orsequencing of library members that include a set of subgenomic intervalsfrom the tumor sample, wherein the subgenomic intervals are chosen fromone, two, three, four, five, ten, fifteen or all of the alterationsdescribed in Table 1B.

In one embodiment, the subgenomic interval includes an alterationclassified in one or more of Category A, B, C, D or E.

In other embodiments, the subgenomic interval includes an alteration inKRAS G13D in a tumor sample, for example, a colon, lung or breast tumorsample.

In other embodiments, the subgenomic interval includes an alteration inNRAS Q61K in a tumor sample, for example, a melanoma or colon tumorsample.

In yet other embodiments, the subgenomic interval includes an alterationin BRAF V600E in a tumor sample, for example, a melanoma, colon, or lungtumor sample.

In other embodiments, the subgenomic interval includes an alteration inBRAF D594G in a tumor sample, for example, a lung tumor sample.

In other embodiments, the subgenomic interval includes an alteration inPIK3CA H1047R in a tumor sample, for example, a breast or colon tumorsample.

In yet other embodiments, the subgenomic interval includes an alterationin EGFR L858R or T790M in a tumor sample, for example, a lung tumorsample.

In other embodiments, the subgenomic interval includes an alteration inERBB2 in a tumor sample, for example, an ERBB2 amplification in a breasttumor sample.

In other embodiments, the subgenomic interval includes an alteration inBRCA1 in a tumor sample, for example, a BRCA1 biallelic inactivation ina breast tumor sample.

In other embodiments, the subgenomic interval includes an alteration inBRCA2 in a tumor sample, for example, a BRCA2 biallelic inactivation ina pancreatic tumor sample.

In other embodiments, the subgenomic interval includes an alteration inATM in a tumor sample, for example, an ATM biallelic inactivation in abreast tumor sample.

In other embodiments, the subgenomic interval includes an alteration inTSC in a tumor sample, for example, a TSC biallelic inactivation in acolon tumor sample.

In other embodiments, the subgenomic interval includes an alteration inPTEN in a tumor sample, for example, a PTEN biallelic inactivation in abreast or colon tumor sample.

In yet other embodiments, the subgenomic interval includes an alterationin VHL in a tumor sample, for example, a VHL biallelic inactivation in akidney tumor sample.

In other embodiments, the subgenomic interval includes an alteration inATR in a tumor sample, for example, an ATR biallelic inactivation in abreast tumor sample.

In other embodiments, the subgenomic interval includes an alteration inMYC in a tumor sample, for example, a MYC biallelic inactivation in abreast tumor sample.

These and other sets and groups of subgenomic intervals are discussed inmore detail elsewhere herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts the typical set-up of a template library leading toselection of desired templates with the hybrid capture method.

FIG. 2A depicts conventional oligonucleotide blocking strategy usingoligonucleotides 102 as blockers to hybridize to the correspondingadaptor 102 sequences found in templates 203 under temperatureconditions that are favorable for 102:102 duplex formation. Note thatmultiple templates 203 are captured via binding of one oligonucleotidebait 204 and its interaction to a capture reagent on an immobilizedsupport 205.

FIG. 2B depicts the T_(m)-enhanced oligonucleotide blocking strategy forenrichment of desired DNA targets without co-selection of unwanted DNAsequences from the complex pool of NGS templates. Rather than usingoligonucleotides 102 as blockers, the strategy uses T_(m)-enhancedoligonucleotides 202 as blockers to hybridize to the correspondingadaptor 102 sequences found in templates 203 under temperatureconditions that are favorable for 202:102 duplex formation. Because202:102 duplexes are favored over 102:102 duplexes at temperatures nearthe optimal enhanced T_(m) value, fewer undesired templates 203 arecaptured via binding of one oligonucleotide bait 204 and its interactionto a capture reagent on an immobilized support 205.

FIG. 3A-3F is a flowchart depiction of an embodiment of a method formultigene analysis of a tumor sample.

FIG. 3A depicts a flowchart depiction of an embodiment for samplereceipt, quality control and DNA isolation.

FIG. 3B depicts a flowchart depiction of an embodiment for DNA qualitycontrol and library generation.

FIG. 3C depicts a flowchart depiction of an embodiment for hybridcapture and sequencing.

FIG. 3D depicts a flowchart depiction of an embodiment for sequence dataquality control and mutation calling.

FIG. 3E depicts a flowchart depiction of an embodiment for reportgeneration.

FIG. 3F depicts a flowchart depiction of an embodiment for additionaldetails of report generation.

FIG. 4 depicts the impact of prior expectation and read depth onmutation detection.

FIG. 5 depicts the mutation frequencies in more than 100 clinical cancersamples.

FIG. 6 is a linear representation of a coverage histogram. The number oftargets (y-axis) are depicted as a function of coverage (x-axis). Line#1 represents the coverage using a bait set that includes biotinylated,array-derived RNA oligonucleotide baits spiked with biotinylated,individually synthesized DNA oligonucleotide baits (referred to hereinas “Bait set #1”). Line #2 represents the coverage obtained using a baitset that includes biotinylated, array-derived RNA oligonucleotide baitsonly (referred to herein as “Bait set #2”). The overall average coverageusing Bait set #2 was 924, whereas the coverage in areas of high GCcontent (about 68%) using Bait set #2 was 73. In contrast, when Bait set#1 was used, the overall coverage was about 918, but the coverage wasimproved to 183 in areas of high GC content.

FIG. 7 is a coverage histogram comparing the uniformity in coveragedetected with a bait set consisting of biotinylated, individuallysynthesized DNA oligonucleotide baits only (Bait set #1) and a bait setthat includes biotinylated, array-derived RNA oligonucleotide baitsspiked with biotinylated, individually synthesized DNA oligonucleotidebaits (“Bait set #2”), compared to a bait set that includesbiotinylated, array-derived RNA oligonucleotide baits only (“Bait set#3”). The bait sets are shown as #1, 2, and 3 in FIG. 7. Several gaps incoverage were detected using Bait set #3, but were not detected usingBait sets #1-2, as depicted in FIG. 7.

FIG. 8 illustrates in diagram form an exemplary configuration ofnon-target concatemers of the library members. The non-target regions(for example, adaptors depicted as “P5” and “P7”) are shown ashybridizing to their complementary non-target strands (depicted as“rcP5” and “rcP7,” respectively). A biotin-tagged bait is shownhybridizing to a complementary region of the target insert of thelibrary member.

FIG. 9 is a bar graph depicting the percentage of target selection usingstandard and extended blocking oligos.

FIG. 10 depicts an exon coverage histogram showing capture results usingstandard or extended blockers.

DETAILED DESCRIPTION OF THE INVENTION

Certain terms are first defined. Additional terms are defined throughoutthe specification.

Terms used herein are intended as “open” terms (for example, the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.).

Furthermore, in those instances where a convention analogous to “atleast one of A,B and C, etc.” is used, in general such a construction isintended in the sense of one having ordinary skill in the art wouldunderstand the convention (for example, “a system having at least one ofA, B and C” would include but not be limited to systems that have Aalone, B alone, C alone, A and B together, A and C together, B and Ctogether, and/or A, B, and C together.). It will be further understoodby those within the art that virtually any disjunctive word and/orphrase presenting two or more alternative terms, whether in thedescription or figures, should be understood to contemplate thepossibilities of including one of the terms, either of the terms, orboth terms. For example, the phrase “A or B” will be understood toinclude the possibilities of “A” or ‘B or “A and B.”

All language such as “from,” “to,” “up to,” “at least,” “greater than,”“less than,” and the like, include the number recited and refer toranges which can subsequently be broken down into sub-ranges asdiscussed above.

A range includes each individual member. Thus, for example, a grouphaving 1-3 members refers to groups having 1, 2, or 3 members.Similarly, a group having 6 members refers to groups having 1, 2, 3, 4,or 6 members, and so forth.

The modal verb “may” refers to the preferred use or selection of one ormore options or choices among the several described embodiments orfeatures contained within the same. Where no options or choices aredisclosed regarding a particular embodiment or feature contained in thesame, the modal verb “may” refers to an affirmative act regarding how tomake or use and aspect of a described embodiment or feature contained inthe same, or a definitive decision to use a specific skill regarding adescribed embodiment or feature contained in the same. In this lattercontext, the modal verb “may” has the same meaning and connotation asthe auxiliary verb “can.”

As used herein, the articles “a” and “an” refer to one or to more thanone (for example, to at least one) of the grammatical object of thearticle.

“About” and “approximately” shall generally mean an acceptable degree oferror for the quantity measured given the nature or precision of themeasurements. Exemplary degrees of error are within 20-25 percent (%),typically, within 10%, and more typically, within 5% of a given value orrange of values.

“Acquire” or “acquiring” as the terms are used herein, refer toobtaining possession of a physical entity, or a value, for example, anumerical value, by “directly acquiring” or “indirectly acquiring” thephysical entity or value. “Directly acquiring” means performing aprocess (for example, performing a synthetic or analytical method) toobtain the physical entity or value. “Indirectly acquiring” refers toreceiving the physical entity or value from another party or source (forexample, a third party laboratory that directly acquired the physicalentity or value). Directly acquiring a physical entity includesperforming a process that includes a physical change in a physicalsubstance, for example, a starting material. Exemplary changes includemaking a physical entity from two or one starting materials, shearing orfragmenting a substance, separating or purifying a substance, combiningtwo or more separate entities into a mixture, performing a chemicalreaction that includes breaking or forming a covalent or non-covalentbond. Directly acquiring a value includes performing a process thatincludes a physical change in a sample or another substance, forexample, performing an analytical process which includes a physicalchange in a substance, for example, a sample, analyte, or reagent(sometimes referred to herein as “physical analysis”), performing ananalytical method, for example, a method which includes one or more ofthe following: separating or purifying a substance, for example, ananalyte, or a fragment or other derivative thereof, from anothersubstance; combining an analyte, or fragment or other derivativethereof, with another substance, for example, a buffer, solvent, orreactant; or changing the structure of an analyte, or a fragment orother derivative thereof, for example, by breaking or forming a covalentor non-covalent bond, between a first and a second atom of the analyte;or by changing the structure of a reagent, or a fragment or otherderivative thereof, for example, by breaking or forming a covalent ornon-covalent bond, between a first and a second atom of the reagent.

“Acquiring a sequence” or “acquiring a read” as the term is used herein,refers to obtaining possession of a nucleotide sequence or amino acidsequence, by “directly acquiring” or “indirectly acquiring” the sequenceor read. “Directly acquiring” a sequence or read means performing aprocess (for example, performing a synthetic or analytical method) toobtain the sequence, such as performing a sequencing method (forexample, a Next Generation Sequencing (NGS) method). “Indirectlyacquiring” a sequence or read refers to receiving information orknowledge of, or receiving, the sequence from another party or source(for example, a third party laboratory that directly acquired thesequence). The sequence or read acquired need not be a full sequence,for example, sequencing of at least one nucleotide, or obtaininginformation or knowledge, that identifies one or more of the alterationsdisclosed herein as being present in a subject constitutes acquiring asequence.

Directly acquiring a sequence or read includes performing a process thatincludes a physical change in a physical substance, for example, astarting material, such as a tissue or cellular sample, for example, abiopsy, or an isolated nucleic acid (for example, DNA or RNA) sample.Exemplary changes include making a physical entity from two or morestarting materials, shearing or fragmenting a substance, such as agenomic DNA fragment; separating or purifying a substance (for example,isolating a nucleic acid sample from a tissue); combining two or moreseparate entities into a mixture, performing a chemical reaction thatincludes breaking or forming a covalent or non-covalent bond. Directlyacquiring a value includes performing a process that includes a physicalchange in a sample or another substance as described above.

“Acquiring a sample” as the term is used herein, refers to obtainingpossession of a sample, for example, a tissue sample or nucleic acidsample, by “directly acquiring” or “indirectly acquiring” the sample.“Directly acquiring a sample” means performing a process (for example,performing a physical method such as a surgery or extraction) to obtainthe sample. “Indirectly acquiring a sample” refers to receiving thesample from another party or source (for example, a third partylaboratory that directly acquired the sample). Directly acquiring asample includes performing a process that includes a physical change ina physical substance, for example, a starting material, such as atissue, for example, a tissue in a human patient or a tissue that haswas previously isolated from a patient. Exemplary changes include makinga physical entity from a starting material, dissecting or scraping atissue; separating or purifying a substance (for example, a sampletissue or a nucleic acid sample); combining two or more separateentities into a mixture; performing a chemical reaction that includesbreaking or forming a covalent or non-covalent bond. Directly acquiringa sample includes performing a process that includes a physical changein a sample or another substance, for example, as described above.

“Alteration” or “altered structure” as used herein, of a gene or geneproduct (for example, a marker gene or gene product) refers to thepresence of a mutation or mutations within the gene or gene product, forexample, a mutation, which affects amount or activity of the gene orgene product, as compared to the normal or wild-type gene. Thealteration can be in amount, structure, and/or activity in a cancertissue or cancer cell, as compared to its amount, structure, and/oractivity, in a normal or healthy tissue or cell (for example, acontrol), and is associated with a disease state, such as cancer. Forexample, an alteration which is associated with cancer, or predictive ofresponsiveness to anti-cancer therapeutics, can have an alterednucleotide sequence (for example, a mutation), amino acid sequence,chromosomal translocation, intra-chromosomal inversion, copy number,expression level, protein level, protein activity, or methylationstatus, in a cancer tissue or cancer cell, as compared to a normal,healthy tissue or cell. Exemplary mutations include, but are not limitedto, point mutations (for example, silent, missense, or nonsense),deletions, insertions, inversions, linking mutations, duplications,translocations, inter- and intra-chromosomal rearrangements. Mutationscan be present in the coding or non-coding region of the gene. Incertain embodiments, the alteration(s) is detected as a rearrangement,for example, a genomic rearrangement comprising one or more introns orfragments thereof (for example, one or more rearrangements in the 5′-and/or 3′-UTR). In certain embodiments, the alterations are associated(or not associated) with a phenotype, for example, a cancerous phenotype(for example, one or more of cancer risk, cancer progression, cancertreatment or resistance to cancer treatment). In one embodiment, thealteration is associated with one or more of: a genetic risk factor forcancer, a positive treatment response predictor, a negative treatmentresponse predictor, a positive prognostic factor, a negative prognosticfactor, or a diagnostic factor.

“Bait”, as used herein, is type of hybrid capture reagent. A bait can bea nucleic acid molecule, for example, a DNA or RNA molecule, which canhybridize to (for example, be complementary to), and thereby allowcapture of a target nucleic acid. In one embodiment, a bait is an RNAmolecule (for example, a naturally-occurring or modified RNA molecule);a DNA molecule (for example, a naturally-occurring or modified DNAmolecule), or a combination thereof. In other embodiments, a baitincludes a binding entity, for example, an affinity tag, that allowscapture and separation, for example, by binding to a binding entity, ofa hybrid formed by a bait and a nucleic acid hybridized to the bait. Inone embodiment, a bait is suitable for solution phase hybridization.

“Bait set,” as used herein, refers to one or a plurality of baitmolecules.

“Binding entity” means any molecule to which molecular tags can bedirectly or indirectly attached that is capable of specifically bindingto an analyte. The binding entity can be an affinity tag on each baitsequence. In certain embodiments, the binding entity allows forseparation of the bait/member hybrids from the hybridization mixture bybinding to a partner, such as an avidin molecule, or an antibody thatbinds to the hapten or an antigen-binding fragment thereof. Exemplarybinding entities include, but are not limited to, a biotin molecule, ahapten, an antibody, an antibody binding fragment, a peptide, and aprotein.

“Complementary” refers to sequence complementarity between regions oftwo nucleic acid strands or between two regions of the same nucleic acidstrand. It is known that an adenine residue of a first nucleic acidregion is capable of forming specific hydrogen bonds (“base pairing”)with a residue of a second nucleic acid region which is antiparallel tothe first region if the residue is thymine or uracil. Similarly, it isknown that a cytosine residue of a first nucleic acid strand is capableof base pairing with a residue of a second nucleic acid strand which isantiparallel to the first strand if the residue is guanine. A firstregion of a nucleic acid is complementary to a second region of the sameor a different nucleic acid if, when the two regions are arranged in anantiparallel fashion, at least one nucleotide residue of the firstregion is capable of base pairing with a residue of the second region.In certain embodiments, the first region comprises a first portion andthe second region comprises a second portion, whereby, when the firstand second portions are arranged in an antiparallel fashion, at leastabout 50%, at least about 75%, at least about 90%, or at least about 95%of the nucleotide residues of the first portion are capable of basepairing with nucleotide residues in the second portion. In otherembodiments, all nucleotide residues of the first portion are capable ofbase pairing with nucleotide residues in the second portion.

The term “cancer” or “tumor” is used interchangeably herein. These termsrefer to the presence of cells possessing characteristics typical ofcancer-causing cells, such as uncontrolled proliferation, immortality,metastatic potential, rapid growth and proliferation rate, and certaincharacteristic morphological features. Cancer cells are often in theform of a tumor, but such cells can exist alone within an animal, or canbe a non-tumorigenic cancer cell, such as a leukemia cell. These termsinclude a solid tumor, a soft tissue tumor, or a metastatic lesion. Asused herein, the term “cancer” includes premalignant, as well asmalignant cancers.

“Likely to” or “increased likelihood,” as used herein, refers to anincreased probability that an item, object, thing or person will occur.Thus, in one example, a subject that is likely to respond to treatmenthas an increased probability of responding to treatment relative to areference subject or group of subjects.

“Unlikely to” refers to a decreased probability that an event, item,object, thing or person will occur with respect to a reference. Thus, asubject that is unlikely to respond to treatment has a decreasedprobability of responding to treatment relative to a reference subjector group of subjects.

“Control member” refers to a member having sequence from a non-tumorcell.

“Indel alignment sequence selector,” as used herein, refers to aparameter that allows or directs the selection of a sequence to which aread is to be aligned with in the case of a preselected indel. Use ofsuch a sequence can optimize the sequencing of a preselected subgenomicinterval comprising an indel. The value for an indel alignment sequenceselector is a function of a preselected indel, for example, anidentifier for the indel. In an embodiment the value is the identity ofthe indel.

As used herein, the term “library” refers to a collection of members. Inone embodiment, the library includes a collection of nucleic acidmembers, for example, a collection of whole genomic, subgenomicfragments, cDNA, cDNA fragments, RNA, RNA fragments, or a combinationthereof. In one embodiment, a portion or all of the library memberscomprises a non-target adaptor sequence. The adaptor sequence can belocated at one or both ends. The adaptor sequence can be useful, forexample, for a sequencing method (for example, an NGS method), foramplification, for reverse transcription, or for cloning into a vector.

The library can comprise a collection of members, for example, a targetmember (for example, a tumor member, a reference member, a PGx member,or a combination thereof). The members of the library can be from asingle individual. In embodiments, a library can comprise members frommore than one subject (for example, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30or more subjects), for example, two or more libraries from differentsubjects can be combined to from a library having members from more thanone subject. In one embodiment, the subject is human having, or at riskof having, a cancer or tumor.

“Library-catch” refers to a subset of a library, for example, a subsetenriched for preselected subgenomic intervals, for example, productcaptured by hybridization with preselected baits.

“Member” or “library member” or other similar term, as used herein,refers to a nucleic acid molecule, for example, a DNA, RNA, or acombination thereof, that is the member of a library. Typically, amember is a DNA molecule, for example, genomic DNA or cDNA. A member canbe fragmented, for example, sheared or enzymatically prepared, genomicDNA. Members comprise sequence from a subject and can also comprisesequence not derived from the subject, for example, a non-targetsequence such as adaptors sequence, a primer sequence, or othersequences that allow for identification, for example, “barcode”sequences.

“Next-generation sequencing or NGS or NG sequencing” as used herein,refers to any sequencing method that determines the nucleotide sequenceof either individual nucleic acid molecules (for example, in singlemolecule sequencing) or clonally expanded proxies for individual nucleicacid molecules in a high through-put fashion (for example, greater than10³, 10⁴, 10⁵ or more molecules are sequenced simultaneously). In oneembodiment, the relative abundance of the nucleic acid species in thelibrary can be estimated by counting the relative number of occurrencesof their cognate sequences in the data generated by the sequencingexperiment. Next generation sequencing methods are known in the art, andare described, for example, in Metzker, M. (2010) Nature BiotechnologyReviews 11:31-46, incorporated herein by reference. Next generationsequencing can detect a variant present in less than 5% of the nucleicacids in a sample.

“Nucleotide value” as referred herein, represents the identity of thenucleotide(s) occupying or assigned to a preselected nucleotideposition. Typical nucleotide values include: missing (for example,deleted); additional (for example, an insertion of one or morenucleotides, the identity of which may or may not be included); orpresent (occupied); A; T; C; or G. Other values can be, for example, notY, wherein Y is A, T, G, or C; A or X, wherein X is one or two of T, G,or C; T or X, wherein X is one or two of A, G, or C; G or X, wherein Xis one or two of T, A, or C; C or X, wherein X is one or two of T, G, orA; a pyrimidine nucleotide; or a purine nucleotide. A nucleotide valuecan be a frequency for 1 or more, for example, 2, 3, or 4, bases (orother value described herein, for example, missing or additional) at anucleotide position. For example, a nucleotide value can comprise afrequency for A, and a frequency for G, at a nucleotide position.

“Or” is used herein to mean, and is used interchangeably with, the term“and/or”, unless context clearly indicates otherwise. The use of theterm “and/or” in some places herein does not mean that uses of the term“or” are not interchangeable with the term “and/or” unless the contextclearly indicates otherwise.

“Primary control” refers to a non-tumor tissue other than NAT tissue ina tumor sample.

Blood is a typical primary control.

“Rearrangement alignment sequence selector,” as used herein, refers to aparameter that allows or directs the selection of a sequence to which aread is to be aligned with in the case of a preselected rearrangement.Use of such a sequence can optimize the sequencing of a preselectedsubgenomic interval comprising a rearrangement. The value for arearrangement alignment sequence selector is a function of a preselectedrearrangement, for example, an identifier for the rearrangement. In anembodiment the value is the identity of the rearrangement. An “indelalignment sequence selector” (also defined elsewhere herein) is anexample of a rearrangement alignment sequence selector.

“Sample,” “tissue sample,” “patient sample,” “patient cell or tissuesample” or “specimen” each refers to a collection of similar cellsobtained from a tissue, or circulating cells, of a subject or patient.The source of the tissue sample can be solid tissue as from a fresh,frozen and/or preserved organ, tissue sample, biopsy, or aspirate; bloodor any blood constituents; bodily fluids such as cerebral spinal fluid,amniotic fluid, peritoneal fluid or interstitial fluid; or cells fromany time in gestation or development of the subject. The tissue samplecan contain compounds that are not naturally intermixed with the tissuein nature such as preservatives, anticoagulants, buffers, fixatives,nutrients, antibiotics or the like. In one embodiment, the sample ispreserved as a frozen sample or as formaldehyde- orparaformaldehyde-fixed paraffin-embedded (FFPE) tissue preparation. Forexample, the sample can be embedded in a matrix, for example, an FFPEblock or a frozen sample.

In one embodiment, the sample is a tumor sample, for example, includesone or more premalignant or malignant cells. In certain, embodiments,the sample, for example, the tumor sample, is acquired from a solidtumor, a soft tissue tumor or a metastatic lesion. In other embodiments,the sample, for example, the tumor sample, includes tissue or cells froma surgical margin. In another embodiment, the sample, for example, tumorsample, includes one or more circulating tumor cells (CTC) (for example,a CTC acquired from a blood sample).

“Sensitivity,” as used herein, is a measure of the ability of a methodto detect a preselected sequence variant in a heterogeneous populationof sequences. A method has a sensitivity of S % for variants of F % if,given a sample in which the preselected sequence variant is present asat least F % of the sequences in the sample, the method can detect thepreselected sequence at a preselected confidence of C %, S % of thetime. By way of example, a method has a sensitivity of 90% for variantsof 5% if, given a sample in which the preselected variant sequence ispresent as at least 5% of the sequences in the sample, the method candetect the preselected sequence at a preselected confidence of 99%, 9out of 10 times (F=5%; C=99%; S=90%). Exemplary sensitivities includethose of S=90%, 95%, 99% for sequence variants at F=1%, 5%, 10%, 20%,50%, 100% at confidence levels of C=90%, 95%, 99%, and 99.9%.

“Specificity,” as used herein, is a measure of the ability of a methodto distinguish a truly occurring preselected sequence variant fromsequencing artifacts or other closely related sequences. It is theability to avoid false positive detections. False positive detectionscan arise from errors introduced into the sequence of interest duringsample preparation, sequencing error, or inadvertent sequencing ofclosely related sequences like pseudo-genes or members of a gene family.A method has a specificity of X % if, when applied to a sample set ofN_(Total) sequences, in which X_(True) sequences are truly variant andX_(Not true) are not truly variant, the method selects at least X % ofthe not truly variant as not variant. For example, a method has aspecificity of 90% if, when applied to a sample set of 1,000 sequences,in which 500 sequences are truly variant and 500 are not truly variant,the method selects 90% of the 500 not truly variant sequences as notvariant. Exemplary specificities include 90, 95, 98, and 99%.

A “tumor nucleic acid sample” as used herein, refers to nucleic acidmolecules from a tumor or cancer sample. Typically, it is DNA, forexample, genomic DNA, or cDNA derived from RNA, from a tumor or cancersample. In certain embodiments, the tumor nucleic acid sample ispurified or isolated (for example, it is removed from its naturalstate).

A “control” or “reference” “nucleic acid sample” as used herein, refersto nucleic acid molecules from a control or reference sample. Typically,it is DNA, for example, genomic DNA, or cDNA derived from RNA, notcontaining the alteration or variation in the gene or gene product. Incertain embodiments, the reference or control nucleic acid sample is awild type or a non-mutated sequence. In certain embodiments, thereference nucleic acid sample is purified or isolated (for example, itis removed from its natural state). In other embodiments, the referencenucleic acid sample is from a non-tumor sample, for example, a bloodcontrol, a normal adjacent tumor (NAT), or any other non-canceroussample from the same or a different subject.

“Sequencing” a nucleic acid molecule requires determining the identityof at least 1 nucleotide in the molecule. In embodiments the identity ofless than all of the nucleotides in a molecule are determined. In otherembodiments, the identity of a majority or all of the nucleotides in themolecule is determined.

“Subgenomic interval” as referred to herein, refers to a portion ofgenomic sequence. In an embodiment a subgenomic interval can be a singlenucleotide position, for example, a nucleotide position variants ofwhich are associated (positively or negatively) with a tumor phenotype.In an embodiment a subgenomic interval comprises more than onenucleotide position. Such embodiments include sequences of at least 2,5, 10, 50, 100, 150, or 250 nucleotide positions in length. Subgenomicintervals can comprise an entire gene, or a preselected portion thereof,for example, the coding region (or portions thereof), a preselectedintron (or portion thereof) or exon (or portion thereof). A subgenomicinterval can comprise all or a part of a fragment of a naturallyoccurring, for example, genomic, nucleic acid. For example, a subgenomicinterval can correspond to a fragment of genomic DNA which is subjectedto a sequencing reaction. In embodiments a subgenomic interval iscontinuous sequence from a genomic source. In embodiments a subgenomicinterval includes sequences that are not contiguous in the genome, forexample, it can include junctions formed found at exon-exon junctions incDNA.

In an embodiment, a subgenomic interval comprises or consists of: asingle nucleotide position; an intragenic region or an intergenicregion; an exon or an intron, or a fragment thereof, typically an exonsequence or a fragment thereof; a coding region or a non-coding region,for example, a promoter, an enhancer, a 5′ untranslated region (5′ UTR),or a 3′ untranslated region (3′ UTR), or a fragment thereof; a cDNA or afragment thereof; an SNP; a somatic mutation, a germ line mutation orboth; an alteration, for example, a point or a single mutation; adeletion mutation (for example, an in-frame deletion, an intragenicdeletion, a full gene deletion); an insertion mutation (for example,intragenic insertion); an inversion mutation (for example, anintra-chromosomal inversion); a linking mutation; a linked insertionmutation; an inverted duplication mutation; a tandem duplication (forexample, an intrachromosomal tandem duplication); a translocation (forexample, a chromosomal translocation, a non-reciprocal translocation); arearrangement (for example, a genomic rearrangement (for example, arearrangement of one or more introns, or a fragment thereof; arearranged intron can include a 5′- and/or 3′-UTR); a change in genecopy number; a change in gene expression; a change in RNA levels, or acombination thereof. The “copy number of a gene” refers to the number ofDNA sequences in a cell encoding a particular gene product. Generally,for a given gene, a mammal has two copies of each gene. The copy numbercan be increased, for example, by gene amplification or duplication, orreduced by deletion.

“Threshold value,” as used herein, is a value that is a function of thenumber of reads required to be present to assign a nucleotide value to asubgenomic interval. For example, it is a function of the number ofreads having a specific nucleotide value, for example, A, at anucleotide position, required to assign that nucleotide value to thatnucleotide position in the subgenomic interval. The threshold value can,for example, be expressed as (or as a function of) a number of reads,for example, an integer, or as a proportion of reads having thepreselected value. By way of example, if the threshold value is X, andX+1 reads having the nucleotide value of “A” are present, then the valueof “A” is assigned to the preselected position in the subgenomicinterval. The threshold value can also be expressed as a function of amutation or variant expectation, mutation frequency, or of Bayesianprior. In an embodiment, a preselected mutation frequency would requirea preselected number or proportion of reads having a nucleotide value,for example, A or G, at a preselected position, to call that thatnucleotide value. In embodiments the threshold value can be a functionof mutation expectation, for example, mutation frequency, and tumortype. For example, a preselected variant at a preselected nucleotideposition could have a first threshold value if the patient has a firsttumor type and a second threshold value if the patient has a secondtumor type.

As used herein, “target member” refers to a nucleic acid molecule thatone desires to isolate from the nucleic acid library. In one embodiment,the target members can be a tumor member, a reference member, a controlmember, or a PGx member as described herein.

“Tumor member,” or other similar term (for example, a “tumor orcancer-associated member”), as used herein refers to a member havingsequence from a tumor cell. In one embodiment, the tumor member includesa subgenomic interval having a sequence (for example, a nucleotidesequence) that has an alteration (for example, a mutation) associatedwith a cancerous phenotype. In other embodiments, the tumor memberincludes a subgenomic interval having a wild type sequence (for example,a wild type nucleotide sequence). For example, a subgenomic intervalfrom a heterozygous or homozygous wild type allele present in a cancercell. A tumor member can include a reference member or a PGx member.

“Reference member,” or other similar term (for example, a “controlmember”), as used herein, refers to a member that comprises a subgenomicinterval having a sequence (for example, a nucleotide sequence) that isnot associated with the cancerous phenotype. In one embodiment, thereference member includes a wild-type or a non-mutated nucleotidesequence of a gene or gene product that when mutated is associated withthe cancerous phenotype. The reference member can be present in a cancercell or non-cancer cell.

“PGx member” or other similar term, as used herein, refers to a memberthat comprises a subgenomic interval that is associated with thepharmacogenetic or pharmacogenomic profile of a gene. In one embodiment,the PGx member includes an SNP (for example, an SNP as describedherein). In other embodiments, the PGx member includes a subgenomicinterval according to Table 1 or Table 2.

As used herein, a “universal nucleobase” refers to a nucleobase thatexhibits the ability to replace any of the four normal nucleobaseswithout significantly destabilizing neighboring base-pair interactions.When such mixed nucleobase compositions, including universal nucleobasecompositions, are present in blockers, they occupy a plurality ofsubstantially contiguous nucleotide positions ranging in lengthspreferably from about 5 to about 12 nucleotides.

“Variant,” as used herein, refers to a structure that can be present ata subgenomic interval that can have more than one structure, forexample, an allele at a polymorphic locus.

Headings, for example, (a), (b), (i) etc., are presented merely for easeof reading the specification and claims. The use of headings in thespecification or claims does not require the steps or elements beperformed in alphabetical or numerical order or the order in which theyare presented.

The invention pertains to novel T_(m)-enhanced oligonucleotides asblockers and baits to improve target enrichment and to reduce off-targetselection. The oligonucleotide compositions have robust applicationpreparing nucleic acid templates for next generation sequencingapplications. The oligonucleotides are modified with T_(m)-enhancinggroups to increase the binding affinity of the oligonucleotides to theirrespective targets that permits hybridization/capture reactions to berun at higher temperatures and under more stringent wash conditions thanunmodified oligonucleotides. For oligonucleotide blockers having theidentical sequence to the terminal adaptors of NGS templates, inclusionof T_(m)-enhanced oligonucleotides as blockers in the hybrid capturemethod reduces the level of unwanted contaminating sequences resultingfrom adaptor-mediated hybrid formation among NGS templates (the“daisy-chain effect”), thereby increasing the overall efficiency of theenrichment process for the desired NGS templates. Compositions of novelT_(m)-enhanced oligonucleotides as blockers and baits as well as theirspecific use for improved target enrichment and for reduced off-targetselection, including their use in applications such as in massivelyparallel sequencing experiments, are disclosed in further detail below.

Referring to FIG. 1, input DNA 100 is fragmented to provide appropriatesize ranges. Preferred size ranges for the resultant DNA fragments 101will depend upon the particular application and/or NGS platform, buttypically range from 200-500 bp in length. The preferred method offragmenting DNA 100 is by shearing the DNA using sonication procedures.Commercially available sonifiers and other sonication instrumentationcan be used to fragment DNA 100 to the appropriate size ranges. Whilefragmenting DNA 100 by shearing is preferred fragmentation means, otherfragmentation procedures can be used, such as partial digestion of DNA100 using endonucleases (for example, DNAses or restrictionendonucleases).

The resultant DNA fragments 101 are enzymatically treated to prepareflush-ended termini to which oligonucleotide adaptors 102 having atleast one flush-end are ligated to yield the NGS templates 103.Typically, sheared DNA can include a variety of termini, such a flushtermini, 5′-overhang termini, and 3′-overhang termini. Those DNAfragments that include 5′-overhang termini can be made flush-ended byfilling in the recessed 3′-termini using a suitable polymerase (forexample, T4 DNA polymerase, the Large (Klenow) Fragment of DNApolymerase I, Vent DNA polymerase, Deep Vent DNA polymerase, amongothers). Those DNA fragments that include a 3′-overhang can be madeflush-ended by using the 3′ 45′ exonuclease activity of a DNApolymerase, preferably in the presence of dNTPs (for example, T4 DNApolymerase, Large (Klenow) Fragment of DNA polymerase I, Pfu polymerase,among others). DNA fragments having 5′-overhang or 3′-overhang terminican also be made flush-ended using single-strand nucleases (for example,Mung Bean Nuclease, P1 nuclease, Si nuclease, among others). The use ofa DNA polymerase is preferable for use to prepared flush-ended terminifor fragments 101.

Optionally, the resultant fragments 101 can be enzymatically manipulatedto include a single nucleotide overhang (for example, a 3′-dA overhang)that can facilitate ligation with adaptors 102 having at least oneterminus with the complementary single-nucleotide overhang (in the aboveexample, a 3′-dT overhang). Such fragments 101 are typically made withflush-ended termini as described above and then subsequently treatedwith an enzyme having 3′-polymerase (“tailing”) activity (for example,Tth DNA polymerase, Bst DNA polymerase, Taq DNA polymerase, Klenow DNApolymerase (exo⁻), among others).

Furthermore, sheared DNA can include internal breaks (for example,nicks) within one of the two complementary strands that do not result incomplete breakage of the double-stranded DNA structure. Such internalbreaks can be repaired using a DNA polymerase having nick-translationactivity in the presence of dNTPs (for example, T4 DNA polymerase orLarge (Klenow) Fragment of DNA Polymerase I, among others) or in thepresence of a suitable ligase in the presence of ATP (for example, T4DNA ligase). It is preferable to repair any single-stranded breakswithin the sheared DNA of fragments 101 since the final templates 103preferably include two adaptors 102 ligated onto each end of the twocontinuous strands.

Adaptors 102 are preferably designed to include different types oftermini. This preferred design is chosen to provide a single copy ofdouble-stranded adaptor 102 for each end of the resultant templates 103.For fragments 101 enzymatically treated to include flush-ended termini,adaptors 102 are designed to include a first terminus having a flush endand a second terminus having an overhang end. For such adaptors 102, thesecond terminus is further designed to include one or more features thatpreclude ligation to other adaptors 102 (for example, lacking aligase-competent substrate, such as a 5′-phosphate group, 3′-hydroxylgroup, and/or sequence complementarity, among others). For fragments 101enzymatically treated to include single-nucleotide termini, adaptors 102are designed to include a first terminus having a complementarysingle-nucleotide overhang and a second terminus having a different typeof end. Like that described above, the second terminus of the latteradaptors 102 preferably designed to include one or more features thatprecludes ligation to other adaptors 102.

The oligonucleotide composition of adaptors 102 preferably includesconventional nucleobases, wherein the internucleotidyl linkages areconventional phosphodiester moieties. The adaptors 102 preferablyexclude chemical groups that display T_(m)-enhanced properties, asfurther explained below. The preferred lengths of oligonucleotideadaptors 102 range from about 15 nucleotides to about 75 nucleotides.

For certain NGS applications, it is desirable to include “barcode”sequences to enable multiplex sequencing in massively parallelsequencing experiments. For this purpose, adaptors 102 represent thebarcode sequence tags. Preferably, the plurality of substantiallycontiguous nucleotide positions that includes these nucleobases islocated within the oligonucleotide at a central position away from thetermini.

The primary sequence composition of adaptors 102 can depend upon anumber of considerations. One consideration is the NGS platform used forthe massively parallel sequencing experiments. For example, thecommercially available automated instrumentation used for NGSapplications have different libraries of templates 103 containingdifferent adaptors 102, so the selection of primary sequencecompositions for any given commercial NGS instrumentation platform willdepend upon that criterion. Another consideration is the primarysequence compositional design of the complementary T_(m)-enhancedoligonucleotide as the blocker. As will become evident below, certainprimary sequence compositions for the blockers are preferred, which caninfluence design decisions regarding the primary sequence composition ofthe complementary adaptors 102.

Referring to FIG. 2A-B, the principle of T_(m)-enhanced oligonucleotidesas blockers and baits is illustrated for a typical NGS application.Double-stranded templates 203, T_(m)-enhanced oligonucleotide blockers202, biotinylated oligonucleotide baits 204 and C_(o)t-1 DNA® (notshown) are mixed together and heat-denatured at 95° C. in a buffermixture adjusted to include a final concentration of 5× Saline SodiumCitrate buffer (SSC) (or similar hybridization buffer, as are well knownto those with skill in the art) and maintained for 1-3 days at ahybridization temperature below the predicted average T_(m) value forbait:target hybrids. As the hybridization mixture cools from the 95° C.denaturation step to the hybridization step, bait:target hybrids willform. Since the T_(m) of the modified blockers is higher than theunmodified adaptors, blocker: adaptor hybrids will form beforeadaptor:adaptor hybrids form, thereby preventing the formation of “daisychains”. The mixture is then added to a solid support media 205containing streptavidin to permit capture of the 203:204 hybrids. Thesupport media/mixture is washed under successively more stringentconditions (for example, 1×SSC, followed by 0.1×SSC) at a temperaturebelow that of the estimated bait:target T_(m) value and, preferably,above that of the T_(m) value of the unmodified adaptors. Given that theadaptors are usually much shorter than the bait oligomers, bait T_(m) isusually well above that of adaptor T_(m). Because the blockers 202 haveenhanced T_(m) values compared to unmodified adaptors found on thetemplates, the templates 203 will preferentially hybridize to theblockers 202 under the increased hybridization temperatures, therebyminimizing different templates 203 from forming daisy-chained aggregatesthrough their respective adaptor sequences. Following the stringentwashes at the elevated hybridization temperature, one final stringentwash is performed at room temperature and the desired templates arerecovered from the immobilized support 205.

Typical oligonucleotide blockers corresponding to the adaptor sequencescan provide about a 60% enrichment of desired target sequences obtainedfrom hybrid capture. By contrast, the T_(m)-enhanced oligonucleotides asblockers can provide over about 80% enrichment of desired targetsequences obtained from hybrid capture. The resultant improvement intarget enrichment from hybrid capture experiments with theT_(m)-enhanced oligonucleotides as blockers ranges provide over an about30% in increased yield of desired template targets relative to the yieldobtained with unmodified oligonucleotides as blockers.

Various embodiments of the design of T_(m)-enhanced oligonucleotides asblockers and baits are now described. As used herein, a “T_(m)-enhancedoligonucleotide” is an oligonucleotide that includes at least onemodified group (“T_(m)-enhancing group”) that provides an increasedthermal melting temperature value (“enhanced T_(m) value”) for a duplexnucleic acid that includes as a hybridization partner theoligonucleotide relative to a duplex nucleic acid that includes as ahybridization partner an oligonucleotide having identical nucleobasecomposition and unmodified groups.

Numerous T_(m)-enhancing groups may be used in the design ofT_(m)-enhanced oligonucleotides. Examples of suitable T_(m)-enhancinggroups for this purpose include modifications to the nucleobases orribose moieties, including, for example, locked nucleic acids (LNAs),bicyclic nucleic acids (BNAs, such as constrained ethyl nucleic acids,from Isis Pharmaceuticals), C5-modified pyrimidine bases (for example,5-methyl-dC, propynyl pyrimidines, among others). Alternate backbonechemistries can also be employed, such as peptide nucleic acids (PNAs),morpholinos, among others. Non-base modifiers can also be employed toincrease T_(m) (or binding affinity), such as a minor grove binder(MGB), spermine, G-clamp, or a Uaq anthraquinone cap. Many strategies toincrease binding affinity are known to those with skill in the art andthe use of all such modifications is considered within the scope of theinvention.

Preferably, T_(m)-enhanced oligonucleotides include a plurality ofT_(m)-enhancing groups. The preferred number of T_(m)-enhancing groupsis that number which provides an increase in the optimal T_(m) valueunder stringent conditions (0.1×SSC) (“optimal enhanced T_(m) value”) ofat least about 1.4° C. for a duplex DNA containing the T_(m)-enhancedoligonucleotide as one complementary strand. The preferred numberT_(m)-enhancing groups in a T_(m)-enhanced oligonucleotide provides foran optimal enhanced T_(m) value ranging from about 2° C. to about 25° C.

A preferred approach to designing of a T_(m)-enhanced oligonucleotidefor improved template enrichment in hybrid capture methods depends uponthe T_(m)-enhancing groups used in the oligonucleotide. The T_(m) valueof a T_(m)-enhanced oligonucleotide containing any of the aforementionedT_(m)-enhancing groups can be determined using routine empiricalmethods. The use of T_(m)-enhancing groups of LNAs or BNAs is preferredsince reliable methods for accurately predicting the T_(m) value forT_(m)-enhanced oligonucleotides containing these latter T_(m)-enhancinggroups are available that require minimal or reduced empiricalevaluation. An example of one such method for this purpose is providedin U.S Patent Publication No. US 2012/0029891 A1 published Feb. 2, 2012,entitled METHODS FOR PREDICTING STABILITY AND MELTING TEMPERATURES OFNUCLEIC ACID DUPLEXES to Behlke, which is incorporated herein byreference in its entirety.

For certain preferred embodiments, T_(m)-enhanced oligonucleotidesinclude a barcode sequence tag. Barcode elements are often included inone of the two adaptor oligonucleotides attached to the target nucleicacid during library construction. A barcode element is typically 6 baseslong; longer elements are also employed, such as 8 bases or longer.Typically the barcode adaptor comprises only one of the two adaptorsemployed in NGS library preparation, with one adaptor being “unique andcoded” and one adaptor being “universal”. It is also possible to placebarcodes on both adaptors. The use of barcoded adaptors permits multiplesamples to be mixed and processed together in a single multiplexsequencing run, offering significant cost savings and increasedthroughput. Sequences are deconvoluted by analysis after sequencing.Multiplex experiments can involve use of 2, 3, 4 or up to a hundred ormore barcode modified adaptor sequences. As each different barcodeadaptor has a unique sequence, the most effective blockingoligonucleotide(s) would be sequences that are a perfect complementarymatch to each unique barcode adaptor present in the set. This approachensures the highest possible T_(m) for the blockers, since mismatcheswithin the barcode domain between adaptor and blocker will lower T_(m).Therefore, for example, use of 4 barcode adaptors in a 4-plex reactionwould require use of 5 distinct blocking oligonucleotides comprising 4unique sequences for the 4 barcode adaptors and 1 unique sequence forthe common universal adaptor. However, if many distinct barcode adaptorsare employed, this approach may require use of as many as a hundred ormore unique blocking oligonucleotides for high level multiplexexperiments, which is not cost effective. Further, mis-hybridization ofblocker “A” to adaptor “B” will likely occur, lowering the bindingaffinity of the blocking oligonucleotides and decreasing theeffectiveness of the blocking step. One solution is to incorporate a“universal” domain into the blocking oligonucleotide comprising a randomN-mer domain (for example, NNNNNN mixed-base hexamer sequence) at theappropriate location within the adaptor oligonucleotide to span thebarcode domain in the adaptor. With this approach, a single blockingoligonucleotide can be used with a large number of barcoded adaptors.Using a 6-base N-mer domain, 4096 different sequences are present in theblocking oligonucleotide pool. Having this large number of barcodespresent will result in most blocker:adaptor pairs to include mismatchesin the barcode domain. Alternatively, a “universal base” can be employedinstead of N-bases. Universal bases are modified nucleobases thathybridize to some or all natural bases with less thermodynamic cost formismatch than true base mismatches, such as G:A or T:T pairs. Manyuniversal bases exist, such as inosine (“I”), 5-nitroindole (“5-NI”),etc., which are well known to those with skill in the art. Pairing of aninosine domain (IIIIII) with a barcode will on average have a higherT_(m) than a fully mismatched N-mer domain (NNNNNN) Therefore, threeapproaches can be used to make blocking oligonucleotides for barcodeadaptors: 1) synthesize a series of blockers which are perfect match toeach adaptor, 2) synthesize a single blocker with an N-mer domain topair with the barcode domain of the adaptor, or 3) synthesize a singleblocker with a universal base domain to pair with the barcode domain ofthe adaptor. One can calculate a sufficiently accurate estimate of theT_(m) value for a particular T_(m)-enhanced blocking oligonucleotidecontaining LNA or BNA groups with the barcode adaptor by omitting thesequence contribution attributed to the mixed or universal nucleobasesequences with the aforementioned method. The precise T_(m) value forsuch oligonucleotides can then be determined with greater precisionusing routine empirical methods.

As mentioned previously, adaptors 102 are present as two complementarystrands on templates 103. Following denaturation of the population ofdouble-stranded templates 103 for hybrid capture, each single-strandedtemplate 103 will include a corresponding single-stranded copy ofadaptor 102. To prevent interactions among different single-strandedtemplates 103 that result in the daisy-chain aggregate of many unrelatedtemplates 103, only one of the two adaptor 102 strands need be blockedfor hybridization with another complementary strand adaptor 102. Forthis reason, and in preferred embodiments, only one T_(m)-enhancedoligonucleotide strand as blocker needs to be included to achieveimproved template enrichment in hybrid capture methods with NGStemplates 103.

The design of the primary sequence of the T_(m)-enhanced oligonucleotideas blocker is based on the primary sequences of one of the twocomplementary strands of oligonucleotide adaptors 102. Though one mayinclude as T_(m)-enhancing groups any or all of the availablenucleobases into a T_(m)-enhanced oligonucleotide, it is preferable toinclude only one single type of modified nucleobase or two differenttypes of modified nucleobases.

Oligonucleotides modified with T_(m)-enhancing nucleobases are atincreased risk for hairpin or self-dimer formation. Oligonucleotidedesign algorithms or calculators can be used to model hairpin and dimerpotential of a sequence and should be used to help screen modificationpatterns. See, for example, the OligoAnalyzer that is publicly availableon the IDT website:http://www.idtdna.com/analyzer/Applications/OligoAnalyzer/. This issueis of particular importance if LNA or BNA modifications are employed.LNA:DNA base pairs show a T_(m) increase relative to DNA:DNA pairs.LNA:LNA base pairs shows a T_(m) increase relative to LNA:DNA pairs. AnyLNA:LNA pairs that occur in hairpin or self-dimer events areparticularly favorable (note that only LNA:DNA pairs can form betweenblockers and targets). Therefore, care must be taken in design ofT_(m)-enhanced oligonucleotides to avoid patterns that promoteself-dimer or hairpin formation via LNA:LNA pairing events. This appliesequally to the BNA modification.

One preferred approach to prevent this problem is to employ only asingle type of modified nucleobase. For example, a T_(m)-enhancedblocking oligonucleotide can be made only using LNA-C or BNA-C.Depending on base composition, complete substitution of a single basetype might not achieve a sufficiently high T_(m) increase to provideoptimal performance. In this case, two different modified nucleobasescan be employed, such as LNA-C with LNA-A, or BNA-C with BNA-A. Ingeneral, modified C can be used with modified A or modified T, but notmodified G. Likewise modified A can be used with modified C or modifiedG, but not modified T. Use of modified C with modified G or use ofmodified A with modified T should be avoided. This strategy limits therisk for increased hairpin/dimer formation by limiting the potentialinteraction between the modified bases. The propynyl pyrimidinemodification is only available as pdU and pdC bases. In this case, amodified blocking oligonucleotide can include one or many pdC bases.Alternatively, the modified blocking oligonucleotide can include amixture of pdC and pdU bases and meet the design criteria previouslyestablished.

For T_(m)-enhanced oligonucleotides, the preferred number ofT_(m)-enhancing groups can vary from about 2% to about 50% ofcomposition of the oligonucleotide. Generally, oligonucleotides servingas blockers will have the same length of one of the two complementarystrands of oligonucleotides used in adaptors 102 (for example, from ˜15to about ˜75 nucleotides in length). For example, the preferred numberof T_(m)-enhancing groups can ranges from 1 to about 25 for aT_(m)-enhanced oligonucleotide as a blocker having 50 nucleotides. Useof a higher fraction of modified residues will incrementally increaseT_(m) and add incremental improvement to the “blocking power” of thatreagent. However, the addition of modified residues increases cost ofthe synthetic oligonucleotide and increases risk of self-dimer andhairpin formation, so judicial use of such groups is recommended. In themajority of NGS applications, only T_(m)-enhanced oligonucleotides asblockers are used to achieve the desired improvements in targetenrichment in massively parallel sequencing experiments.

For T_(m)-enhanced oligonucleotides as baits, the preferred number ofT_(m)-enhancing groups falls within the same range of percentages asdescribed of the oligonucleotides as blockers. Oligonucleotides servingas unmodified baits will range in size from about 60 to about 200nucleotides in length, where the most commonly used bait length is about120 nucleotides in length. By including T_(m)-enhancing groups intooligonucleotides as baits, however, one can use shorter baits that rangefrom about 20 to about 100 nucleotides in length. For certain massivelyparallel sequencing experiments in NGS applications, a population ofhundreds of oligonucleotides is used as baits. So depending upon thenumber of baits required in certain applications, the use of shorter,T_(m)-enhanced oligonucleotides for each bait candidate within thatpopulation can provide economical advantages relative to usingunmodified oligonucleotides as baits.

The T_(m)-enhanced oligonucleotides can include additional features,such as internal or terminal modifications. For T_(m)-enhancedoligonucleotides that serve as blockers, recovery of the desired NGStemplates following hybrid capture can typically result inco-purification of the blockers. The blockers will be substantiallydiluted from the population of templates as subsequent steps of PCRamplification and sequencing proceeds. Yet it is desirable to limit theparticipation of the blockers as primers during these subsequent steps.For this reason, T_(m)-enhanced oligonucleotides can include 3′-terminalgroups (for example, 3′-dC; 2′,3′-ddC; inverted dT; 3′-spacer C3, amongothers) that preclude the availability of the blockers to serve asprimers for DNA synthesis.

Oligonucleotides that serve as baits include at least one modificationthat enables selection of desired template:bait hybrids from thepopulation of templates 103 during hybrid capture. One example of apreferred modification includes biotin that can be incorporated into theoligonucleotide bait during chemical synthesis and used with solidsupport media containing avidin or streptavidin for hybrid selection.Other capture ligands can be employed, such as digoxigenin or othergroups as are well known to those with skill in the art.

Preferred examples of T_(m)-enhanced oligonucleotides as blockersinclude SEQ ID NOS: 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 18,19, 21, 22, 24, 25, 27, 28, 30, 32, 34 and 36. These particularsequences, their compositions and methods of use in massively parallelsequencing applications are described in greater detail in the Examples.

Selection of Gene or Gene Products

The selected genes or gene products (also referred to herein as the“target genes or gene products”) can include subgenomic intervalscomprising intragenic regions or intergenic regions. For example, thesubgenomic interval can include an exon or an intron, or a fragmentthereof, typically an exon sequence or a fragment thereof. Thesubgenomic interval can include a coding region or a non-coding region,for example, a promoter, an enhancer, a 5′ untranslated region (5′ UTR),or a 3′ untranslated region (3′ UTR), or a fragment thereof. In otherembodiments, the subgenomic interval includes a cDNA or a fragmentthereof. In other embodiments, the subgenomic interval includes an SNP,for example, as described herein.

In other embodiments, the subgenomic intervals include substantially allexons in a genome, for example, one or more of the subgenomic intervalsas described herein (for example, exons from selected genes or geneproducts of interest (for example, genes or gene products associatedwith a cancerous phenotype as described herein)). In one embodiment, thesubgenomic interval includes a somatic mutation, a germ line mutation orboth. In one embodiment, the subgenomic interval includes an alteration,for example, a point or a single mutation, a deletion mutation (forexample, an in-frame deletion, an intragenic deletion, a full genedeletion), an insertion mutation (for example, intragenic insertion), aninversion mutation (for example, an intra-chromosomal inversion), alinking mutation, a linked insertion mutation, an inverted duplicationmutation, a tandem duplication (for example, an intrachromosomal tandemduplication), a translocation (for example, a chromosomal translocation,a non-reciprocal translocation), a rearrangement, a change in gene copynumber, or a combination thereof. In certain embodiments, the subgenomicinterval constitutes less than 5, 1, 0.5, 0.1%, 0.01%, 0.001% of thecoding region of the genome of the tumor cells in a sample. In otherembodiments, the subgenomic intervals are not involved in a disease, forexample, are not associated with a cancerous phenotype as describedherein.

In one embodiment, the target gene or gene product is a biomarker. Asused herein, a “biomarker” or “marker” is a gene, mRNA, or protein whichcan be altered, wherein said alteration is associated with cancer. Thealteration can be in amount, structure, and/or activity in a cancertissue or cancer cell, as compared to its amount, structure, and/oractivity, in a normal or healthy tissue or cell (for example, acontrol), and is associated with a disease state, such as cancer. Forexample, a marker associated with cancer, or predictive ofresponsiveness to anti-cancer therapeutics, can have an alterednucleotide sequence, amino acid sequence, chromosomal translocation,intra-chromosomal inversion, copy number, expression level, proteinlevel, protein activity, or methylation status, in a cancer tissue orcancer cell as compared to a normal, healthy tissue or cell.Furthermore, a “marker” includes a molecule whose structure is altered,for example, mutated (contains an mutation), for example, differs fromthe wild type sequence at the nucleotide or amino acid level, forexample, by substitution, deletion, or insertion, when present in atissue or cell associated with a disease state, such as cancer.

In one embodiment, the target gene or gene product includes asingle-nucleotide polymorphism (SNP). In another embodiment, the gene orgene product has a small deletion, for example, a small intragenicdeletion (for example, an in-frame or frame-shift deletion). In yetanother embodiment, the target sequence results from the deletion of anentire gene. In still another embodiment, the target sequence has asmall insertion, for example, a small intragenic insertion. In oneembodiment, the target sequence results from an inversion, for example,an intrachromosal inversion. In another embodiment, the target sequenceresults from an interchromosal translocation. In yet another embodiment,the target sequence has a tandem duplication. In one embodiment, thetarget sequence has an undesirable feature (for example, high GC contentor repeat element). In another embodiment, the target sequence has aportion of nucleotide sequence that cannot itself be successfullytargeted, for example, because of its repetitive nature. In oneembodiment, the target sequence results from alternative splicing. Inanother embodiment, the target sequence is chosen from a gene or geneproduct, or a fragment thereof according to Table 1, 1A, 2, 3, or 4.

Cancers include, but are not limited to, B cell cancer, for example,multiple myeloma, melanomas, breast cancer, lung cancer (such asnon-small cell lung carcinoma or NSCLC), bronchus cancer, colorectalcancer, prostate cancer, pancreatic cancer, stomach cancer, ovariancancer, urinary bladder cancer, brain or central nervous system cancer,peripheral nervous system cancer, esophageal cancer, cervical cancer,uterine or endometrial cancer, cancer of the oral cavity or pharynx,liver cancer, kidney cancer, testicular cancer, biliary tract cancer,small bowel or appendix cancer, salivary gland cancer, thyroid glandcancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, cancer ofhematological tissues, adenocarcinomas, inflammatory myofibroblastictumors, gastrointestinal stromal tumor (GIST), colon cancer, multiplemyeloma (MM), myelodysplastic syndrome (MDS), myeloproliferativedisorder (MPD), acute lymphocytic leukemia (ALL), acute myelocyticleukemia (AML), chronic myelocytic leukemia (CIVIL), chronic lymphocyticleukemia (CLL), polycythemia Vera, Hodgkin lymphoma, non-Hodgkinlymphoma (NHL), soft-tissue sarcoma, fibrosarcoma, myxosarcoma,liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma,endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma,synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma,rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma,adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma,papillary carcinoma, papillary adenocarcinomas, medullary carcinoma,bronchogenic carcinoma, renal cell carcinoma, hepatoma, bile ductcarcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor,bladder carcinoma, epithelial carcinoma, glioma, astrocytoma,medulloblastoma, craniopharyngioma, ependymoma, pinealoma,hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma,neuroblastoma, retinoblastoma, follicular lymphoma, diffuse large B-celllymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroidcancer, gastric cancer, head and neck cancer, small cell cancers,essential thrombocythemia, agnogenic myeloid metaplasia,hypereosinophilic syndrome, systemic mastocytosis, familiarhypereosinophilia, chronic eosinophilic leukemia, neuroendocrinecancers, carcinoid tumors, and the like.

In one embodiment, the target gene or gene product is chosen a fulllength, or a fragment thereof, selected from the group consisting ofABCB1, ABCC2, ABCC4, ABCG2, ABL1, ABL2, AKT1, AKT2, AKT3, ALK, APC, AR,ARAF, ARFRP1, ARID1A, ATM, ATR, AURKA, AURKB, BCL2, BCL2A1, BCL2L1,BCL2L2, BCL6, BRAF, BRCA1, BRCA2, Clorf144, CARD11, CBL, CCND1, CCND2,CCND3, CCNE1, CDH1, CDH2, CDH2O, CDH5, CDK4, CDK6, CDK8, CDKN2A, CDKN2B,CDKN2C, CEBPA, CHEK1, CHEK2, CRKL, CRLF2, CTNNB1, CYP1B1, CYP2C19,CYP2C8, CYP2D6, CYP3A4, CYP3A5, DNMT3A, DOT1L, DPYD, EGFR, EPHA3, EPHA5,EPHA6, EPHA7, EPHB1, EPHB4, EPHB6, ERBB2, ERBB3, ERBB4, ERCC2, ERG,ESR1, ESR2, ETV1, ETV4, ETV5, ETV6, EWSR1, EZH2, FANCA, FBXW7, FCGR3A,FGFR1, FGFR2, FGFR3, FGFR4, FLT1, FLT3, FLT4, FOXP4, GATA1, GNA11, GNAQ,GNAS, GPR124, GSTP1, GUCY1A2, HOXA3, HRAS, HSP9OAA1, IDH1, IDH2, IGF1R,IGF2R, IKBKE, IKZF1, INHBA, IRS2, ITPA, JAK1, JAK2, JAK3, JUN, KDR, KIT,KRAS, LRP1B, LRP2, LTK, MAN1B1, MAP2K1, MAP2K2, MAP2K4, MCL1, MDM2,MDM4, MEN1, MET, MITF, MLH1, MLL, MPL, MRE11A, MSH2, MSH6, MTHFR, MTOR,MUTYH, MYC, MYCL1, MYCN, NF1, NF2, NKX2-1, NOTCH1, NPM1, NQO1, NRAS,NRP2, NTRK1, NTRK3, PAK3, PAX5, PDGFRA, PDGFRB, PIK3CA, PIK3R1, PKHD1,PLCG1, PRKDC, PTCH1, PTEN, PTPN11, PTPRD, RAF1, RARA, RB1, RET, RICTOR,RPTOR, RUNX1, SLC19A1, SLC22A2, SLCO1B3, SMAD2, SMAD3, SMAD4, SMARCA4,SMARCB1, SMO, SOD2, SOX10, SOX2, SRC, STK11, SULT1A1, TBX22, TET2,TGFBR2, TMPRSS2, TOP1, TP53, TPMT, TSC1, TSC2, TYMS, UGT1A1, UMPS,USP9X, VHL, and WT1.

In one embodiment, the target gene or gene product, or a fragmentthereof, has one or more SNPs that are relevant to pharmacogenetics andpharmacogenomics (PGx), for example, drug metabolism and toxicity.Exemplary genes or gene products include, but not limited to, ABCB1,ABCC2, ABCC4, ABCG2, Clorf144, CYP1B1, CYP2C19, CYP2C8, CYP2D6, CYP3A4,CYP3A5, DPYD, ERCC2, ESR2, FCGR3A, GSTP1, ITPA, LRP2, MAN1B1, MTHFR,NQO1, NRP2, SLC19A1, SLC22A2, SLCO1B3, SOD2, SULT1A1, TPMT, TYMS,UGT1A1, and UMPS.

In another embodiment, the target gene or gene product, or a fragmentthereof, has one or more codons that are associated with cancer.Exemplary genes or gene products include, but not limited to, ABL1 (forexample, codon 315), AKT1, ALK, APC (for example, codon 1114, 1338,1450, and 1556), AR, BRAF (for example, codon 600), CDKN2A, CEBPA,CTNNB1 (for example, codon 32, 33, 34, 37, 41, and 45), EGFR (forexample, 719, 746-750, 768, 790, 858, and 861), ERBB2, ESR1, FGFR1,FGFR2, FGFR3, FLT3 (for example, codon 835), HRAS (for example, codon12, 13, and 61), JAK2 (for example, codon 617), KIT (for example, codon816), KRAS (for example, codon 12, 13, and 61), MET, MLL, MYC, NF1,NOTCH1, NPM1, NRAS, PDGFRA, PIK3CA (for example, codon 88, 542, 545,546, 1047, and 1049), PTEN (for example, codon 130, 173, 233, and 267),RB1, RET (for example, codon 918), TP53 (for example, 175, 245, 248,273, and 306).

In yet another embodiment, the target gene or gene product, or afragment thereof, are associated with cancer. Exemplary genes or geneproducts include, but not limited to, ABL2, AKT2, AKT3, ARAF, ARFRP1,ARID1A, ATM, ATR, AURKA, AURKB, BCL2, BCL2A1, BCL2L1, BCL2L2, BCL6,BRCA1, BRCA2, CARD11, CBL, CCND1, CCND2, CCND3, CCNE1, CDH1, CDH2,CDH2O, CDH5, CDK4, CDK6, CDK8, CDKN2B, CDKN2C, CHEK1, CHEK2, CRKL,CRLF2, DNMT3A, DOT1L, EPHA3, EPHA5, EPHA6, EPHA7, EPHB1, EPHB4, EPHB6,ERBB3, ERBB4, ERG, ETV1, ETV4, ETV5, ETV6, EWSR1, EZH2, FANCA, FBXW7,FGFR4, FLT1, FLT4, FOXP4, GATA1, GNA11, GNAQ, GNAS, GPR124, GUCY1A2,HOXA3, HSP9OAA1, IDH1, IDH2, IGF1R, IGF2R, IKBKE, IKZF1, INHBA, IRS2,JAK1, JAK3, JUN, KDR, LRP1B, LTK, MAP2K1, MAP2K2, MAP2K4, MCL1, MDM2,MDM4, MEN1, MITF, MLH1, MPL, MRE11A, MSH2, MSH6, MTOR, MUTYH, MYCL1,MYCN, NF2, NKX2-1, NTRK1, NTRK3, PAK3, PAX5, PDGFRB, PIK3R1, PKHD1,PLCG1, PRKDC, PTCH1, PTPN11, PTPRD, RAF1, RARA, RICTOR, RPTOR, RUNX1,SMAD2, SMAD3, SMAD4, SMARCA4, SMARCB1, SMO, SOX10, SOX2, SRC, STK11,TBX22, TET2, TGFBR2, TMPRSS2, TOP1, TSC1, TSC2, USP9X, VHL, and WT1.

Applications of the foregoing methods include using a library ofoligonucleotides containing all known sequence variants (or a subsetthereof) of a particular gene or genes for sequencing in medicalspecimens.

Nucleic Acid Samples

A variety of tissue samples can be the source of the nucleic acidsamples used in the present methods. Genomic or subgenomic nucleic acid(for example, DNA or RNA) can be isolated from a subject's sample (forexample, a tumor sample, a normal adjacent tissue (NAT), a blood sample,a sample containing circulating tumor cells (CTC) or any normalcontrol)). In certain embodiments, the tissue sample is preserved as afrozen sample or as formaldehyde- or paraformaldehyde-fixedparaffin-embedded (FFPE) tissue preparation. For example, the sample canbe embedded in a matrix, for example, an FFPE block or a frozen sample.The isolating step can include flow-sorting of individual chromosomes;and/or micro-dissecting a subject's sample (for example, a tumor sample,a NAT, a blood sample).

An “isolated” nucleic acid molecule is one which is separated from othernucleic acid molecules which are present in the natural source of thenucleic acid molecule. In certain embodiments, an “isolated” nucleicacid molecule is free of sequences (such as protein-encoding sequences)which naturally flank the nucleic acid (that is, sequences located atthe 5′ and 3′ ends of the nucleic acid) in the genomic DNA of theorganism from which the nucleic acid is derived. For example, in variousembodiments, the isolated nucleic acid molecule can contain less thanabout 5 kB, less than about 4 kB, less than about 3 kB, less than about2 kB, less than about 1 kB, less than about 0.5 kB or less than about0.1 kB of nucleotide sequences which naturally flank the nucleic acidmolecule in genomic DNA of the cell from which the nucleic acid isderived. Moreover, an “isolated” nucleic acid molecule, such as a cDNAmolecule, can be substantially free of other cellular material orculture medium when produced by recombinant techniques, or substantiallyfree of chemical precursors or other chemicals when chemicallysynthesized.

The language “substantially free of other cellular material or culturemedium” includes preparations of nucleic acid molecule in which themolecule is separated from cellular components of the cells from whichit is isolated or recombinantly produced. Thus, nucleic acid moleculethat is substantially free of cellular material includes preparations ofnucleic acid molecule having less than about 30%, less than about 20%,less than about 10%, or less than about 5% (by dry weight) of othercellular material or culture medium.

In certain embodiments, the nucleic acid is isolated from an agedsample, for example, an aged FFPE sample. The aged sample, can be, forexample, years old, for example, 1 year, 2 years, 3 years, 4 years, 5years, 10 years, 15 years, 20 years, 25 years, 50 years, 75 years, or100 years old or older.

A nucleic acid sample can be obtained from tissue samples (for example,a biopsy or FFPE sample) of various sizes. For example, the nucleic acidcan be isolated from a tissue sample from 5 to 200 μm, or larger. Forexample, the tissue sample can measure 5 μm, 10 μm, 20 μm, 30 μm, 40 μm,50 μm, 70 μm, 100 μm, 110 μm, 120 μm, 150 μm or 200 μm or larger.

Protocols for DNA isolation from a tissue sample are provided inExample 1. Additional methods to isolate nucleic acids (for example,DNA) from formaldehyde- or paraformaldehyde-fixed, paraffin-embedded(FFPE) tissues are disclosed, for example, in Cronin M. et al., (2004)Am J Pathol. 164(1):35-42; Masuda N. et al., (1999) Nucleic Acids Res.27(22):4436-4443; Specht K. et al., (2001) Am J Pathol. 158(2):419-429,Ambion RecoverAll™ Total Nucleic Acid Isolation Protocol (Ambion, Cat.No. AM1975, September 2008), Maxwell® 16 FFPE Plus LEV DNA PurificationKit Technical Manual (Promega Literature #TM349, February 2011),E.Z.N.A.® FFPE DNA Kit Handbook (OMEGA bio-tek, Norcross, Ga., productnumbers D3399-00, D3399-01, and D3399-02; June 2009), and QIAamp® DNAFFPE Tissue Handbook (Qiagen, Cat. No. 37625, October 2007). RecoverAll™Total Nucleic Acid Isolation Kit uses xylene at elevated temperatures tosolubilize paraffin-embedded samples and a glass-fiber filter to capturenucleic acids. Maxwell® 16 FFPE Plus LEV DNA Purification Kit is usedwith the Maxwell® 16 Instrument for purification of genomic DNA from 1to 10 μm sections of FFPE tissue. DNA is purified using silica-cladparamagnetic particles (PMPs), and eluted in low elution volume. TheE.Z.N.A.® FFPE DNA Kit uses a spin column and buffer system forisolation of genomic DNA. QIAamp® DNA FFPE Tissue Kit uses QIAamp® DNAMicro technology for purification of genomic and mitochondrialDNA.Protocols for DNA isolation from blood are disclosed, for example,in the Maxwell® 16 LEV Blood DNA Kit and Maxwell 16 Buccal Swab LEV DNAPurification Kit Technical Manual (Promega Literature #TM333, Jan. 1,2011).

Protocols for RNA isolation are disclosed, for example, in the Maxwell®16 Total RNA Purification Kit Technical Bulletin (Promega Literature#TB351, August 2009).

The isolated nucleic acid samples (for example, genomic DNA samples) canbe fragmented or sheared by practicing routine techniques. For example,genomic DNA can be fragmented by physical shearing methods, enzymaticcleavage methods, chemical cleavage methods, and other methods wellknown to those skilled in the art. The nucleic acid library can containall or substantially all of the complexity of the genome. The term“substantially all” in this context refers to the possibility that therecan in practice be some unwanted loss of genome complexity during theinitial steps of the procedure. The methods described herein also areuseful in cases where the nucleic acid library is a portion of thegenome, that is, where the complexity of the genome is reduced bydesign. In some embodiments, any selected portion of the genome can beused with the methods described herein. In certain embodiments, theentire exome or a subset thereof is isolated.

Methods featured in the invention can further include isolating anucleic acid sample to provide a library (for example, a nucleic acidlibrary as described herein). In certain embodiments, the nucleic acidsample includes whole genomic, subgenomic fragments, or both. Theisolated nucleic acid samples can be used to prepare nucleic acidlibraries. Thus, in one embodiment, the methods featured in theinvention further include isolating a nucleic acid sample to provide alibrary (for example, a nucleic acid library as described herein).Protocols for isolating and preparing libraries from whole genomic orsubgenomic fragments are known in the art (for example, Illumina'sgenomic DNA sample preparation kit). In certain embodiments, the genomicor subgenomic DNA fragment is isolated from a subject's sample (forexample, a tumor sample, a normal adjacent tissue (NAT), a blood sampleor any normal control)). In one embodiment, the sample (for example, thetumor or NAT sample) is a preserved specimen. For example, the sample isembedded in a matrix, for example, an FFPE block or a frozen sample. Incertain embodiments, the isolating step includes flow-sorting ofindividual chromosomes; and/or microdissecting a subject's sample (forexample, a tumor sample, a NAT, a blood sample). In certain embodiments,the nucleic acid sample used to generate the nucleic acid library isless than 5 microgram, less than 1 microgram, or less than 500 ng, lessthan 200 ng, less than 100 ng, less than 50 ng, less than 10 ng, lessthan 5 ng, or less than 1 ng.

In still other embodiments, the nucleic acid sample used to generate thelibrary includes RNA or cDNA derived from RNA. In some embodiments, theRNA includes total cellular RNA. In other embodiments, certain abundantRNA sequences (for example, ribosomal RNAs) have been depleted. In someembodiments, the poly(A)-tailed mRNA fraction in the total RNApreparation has been enriched. In some embodiments, the cDNA is producedby random-primed cDNA synthesis methods. In other embodiments, the cDNAsynthesis is initiated at the poly(A) tail of mature mRNAs by priming byoligo(dT)-containing oligonucleotides. Methods for depletion, poly(A)enrichment, and cDNA synthesis are well known to those skilled in theart.

The method can further include amplifying the nucleic acid sample byspecific or non-specific nucleic acid amplification methods that arewell known to those skilled in the art. In some embodiments, certainembodiments, the nucleic acid sample is amplified, for example, bywhole-genome amplification methods such as random-primedstrand-displacement amplification.

In other embodiments, the nucleic acid sample is fragmented or shearedby physical or enzymatic methods and ligated to synthetic adaptors,size-selected (for example, by preparative gel electrophoresis) andamplified (for example, by PCR). In other embodiments, the fragmentedand adaptor-ligated group of nucleic acids is used without explicit sizeselection or amplification prior to hybrid selection.

In other embodiments, the isolated DNA (for example, the genomic DNA) isfragmented or sheared. In some embodiments, the library includes lessthan 50% of genomic DNA, such as a subfraction of genomic DNA that is areduced representation or a defined portion of a genome, for example,that has been subfractionated by other means. In other embodiments, thelibrary includes all or substantially all genomic DNA.

In some embodiments, the library includes less than 50% of genomic DNA,such as a subfraction of genomic DNA that is a reduced representation ora defined portion of a genome, for example, that has beensubfractionated by other means. In other embodiments, the libraryincludes all or substantially all genomic DNA. Protocols for isolatingand preparing libraries from whole genomic or subgenomic fragments areknown in the art (for example, Illumina's genomic DNA sample preparationkit), and are described herein as Examples 2A, 2B and 3. Alternativemethods for DNA shearing are described herein as Example 2B. Forexample, alternative DNA shearing methods can be more automatable and/ormore efficient (for example, with degraded FFPE samples). Alternativesto DNA shearing methods can also be used to avoid a ligation step duringlibrary preparation.

The methods described herein can be performed using a small amount ofnucleic acids, for example, when the amount of source DNA is limiting(for example, even after whole-genome amplification). In one embodiment,the nucleic acid comprises less than about 5 μg, 4 μg, 3 μg, 2 μg, 1 μg,0.8 μg, 0.7 μg, 0.6 μg, 0.5 μg, or 400 ng, 300 ng, 200 ng, 100 ng, 50ng, 10 ng, 5 ng, 1 ng, or less of nucleic acid sample. For example, onecan typically begin with 50-100 ng of genomic DNA. One can start withless, however, if one amplifies the genomic DNA (for example, using PCR)before the hybridization step, for example, solution hybridization. Thusit is possible, but not essential, to amplify the genomic DNA beforehybridization, for example, solution hybridization.

The nucleic acid sample used to generate the library can also includeRNA or cDNA derived from RNA. In some embodiments, the RNA includestotal cellular RNA. In other embodiments, certain abundant RNA sequences(for example, ribosomal RNAs) have been depleted. In other embodiments,the poly(A)-tailed mRNA fraction in the total RNA preparation has beenenriched. In some embodiments, the cDNA is produced by random-primedcDNA synthesis methods. In other embodiments, the cDNA synthesis isinitiated at the poly(A) tail of mature mRNAs by priming byoligo(dT)-containing oligonucleotides. Methods for depletion, poly(A)enrichment, and cDNA synthesis are well known to those skilled in theart.

The method can further include amplifying the nucleic acid sample byspecific or non-specific nucleic acid amplification methods that areknown to those skilled in the art. The nucleic acid sample can beamplified, for example, by whole-genome amplification methods such asrandom-primed strand-displacement amplification.

The nucleic acid sample can be fragmented or sheared by physical orenzymatic methods as described herein, and ligated to syntheticadaptors, size-selected (for example, by preparative gelelectrophoresis) and amplified (for example, by PCR). The fragmented andadaptor-ligated group of nucleic acids is used without explicit sizeselection or amplification prior to hybrid selection.

Library Members

“Member” or “library member” or other similar term, as used herein,refers to a nucleic acid molecule, for example, DNA or RNA, that is themember of a library (or “library-catch”). The library member can be oneor more of a tumor member, a reference member, or a PGx member asdescribed herein. Typically, a member is a DNA molecule, for example, agenomic DNA or cDNA, molecule. A member can be fragmented, for example,enzymatically or by shearing, genomic DNA. Members can comprise anucleotide sequence from a subject and can also comprise a nucleotidesequence not derived from the subject, for example, primers or adaptors(for example, for PCR amplification or for sequencing), or sequencesthat allow for identification of a sample, for example, “barcode”sequences.

As used herein, “target member” refers to a nucleic acid molecule thatone desires to isolate from the nucleic acid library. In one embodiment,the target members can be a tumor member, a reference member, or a PGxmember as described herein. The members that are actually selected fromthe nucleic acid library are referred to herein as the “library catch.”In one embodiment, the library-catch includes a selection or enrichmentof members of the library, for example, the enriched or selected outputof a library after one or more rounds of hybrid capture as describedherein.

The target members may be a subgroup of the library, that is, that notall of the library members are selected by any particular use of theprocesses described herein. In other embodiments, the target members arewithin a desired target region. For example, the target members may insome embodiments be a percentage of the library members that is as lowas 10% or as high as 95%-98% or higher. In one embodiment, the librarycatch includes at least about 20%, 30%, 40%, 50%, 60%, 70%, 75%, 80%,85%, 90%, 95%, 98%, 99%, 99.9% or more of the target members. In anotherembodiment, the library contains 100% of the target members. In oneembodiment, the purity of the library catch (percentage of reads thatalign to the targets) is at least about 20%, 30%, 40%, 50%, 60%, 70%,75%, 80%, 85%, 90%, 95%, 98%, 99%, 99.9% or more.

The target members (or the library catch) obtained from genomic DNA caninclude a small fraction of the total genomic DNA, such that it includesless than about 0.0001%, at least about 0.0001%, at least about 0.001%,at least about 0.01%, or at least about 0.1% of genomic DNA, or a moresignificant fraction of the total genomic DNA, such that it includes atleast about 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, or 10% of genomic DNA,or more than 10% of genomic DNA.

In one embodiment, the target members (or the library catch) areselected from a complex mixture of genome. For example, the selection ofthe DNA from one cell type (for example, cancer cells) from a samplecontaining the DNA from other cell types (for example, normal cells). Insuch applications, the target member can include less than 0.0001%, atleast 0.0001%, at least about 0.001%, at least about 0.01%, or at leastabout 0.1% of the total complexity of the nucleic acid sequences presentin the complex sample, or a more significant fraction such that itincludes at least about 1%, 2%, 5%, 10% or more than 10% of the totalcomplexity of nucleic acid sequences present in the complex sample.

In one embodiment, the target member (or the library catch) selected bythe methods described herein (for example, solution hybridizationselection methods) include all or a portion of exons in a genome, suchas greater than about 0.1%, 1%, 2%, 5%, 10%, 20%, 30%, 40%, 50%, 60%,70%, 80%, 90%, or 95% of the genomic exons. In another embodiment, thetarget member (or the library catch) can be a specific group of exons,for example, at least about 100, 200, 300, 400, 500, 600, 700, 800, 900,or 1000 particular exons, for example, exons associated with particulardiseases such as cancer. In yet another embodiment, the target member(or the library catch) contains exons or other parts of selected genesof interest. The use of specific bait sequences allows the practitionerto select target sequences (ideal set of sequences selected) andsubgroups of nucleic acids (actual set of sequences selected) containingas many or as few exons (or other sequences) from a group of nucleicacids for a particular selection.

In one embodiment, the target member (or the library catch) includes aset of cDNAs. Capturing cDNAs can be used, for example, to find splicevariants, and to identify fusion transcripts (for example, from genomicDNA translocations). In another embodiment, the target member (and thelibrary catch) is used to find single base changes and other sequencechanges expressed in the RNA fraction of a cell, tissue, or organ, forexample, in a tumor.

The target member (or the library catch) (for example, exons, cDNAs andother sequences) can be related or unrelated as desired. For example,selected target member (and the library catch) can be obtained from agroup of nucleic acids that are genes involved in a disease, such as agroup of genes implicated in one or more diseases such as cancers, agroup of nucleic acids containing specific SNPs.

In one embodiment, a portion or all of the library members comprises anon-target adaptor sequence. The adaptor sequence can be useful, forexample, for a sequencing method (for example, an NGS method), foramplification, for reverse transcription, or for cloning into a vector.The adaptor sequence can be located at one or both ends. Adaptors can beligated at the 5′- or 3′-3 end of the library insert, for example, asdescribed in the appended Examples. Adaptors can be obtained fromcommercial suppliers, such as NimbleGen (Roche), Integrated DNATechnologies (IDT) for DNA oligos, or Agilent Technologies.

Blocking oligonucleotide complementary to the adaptors can be designedand prepared by methods known in the art, for example, methods of oligosynthesis. Blocking oligonucleotides can also be obtained fromcommercial suppliers, such as NimbleGen (Roche), Integrated DNATechnologies (IDT) for DNA oligos, or Agilent Technologies. The lengthand composition of these adaptors can be adjusted to, for example,modify the binding interaction (for example, a T_(m) as describedherein) with the complementary adaptor following methods known in theart.

The blocking oligonucleotides can include DNA, RNA or a combination ofboth. The DNA or RNA oligonucleotides can be naturally- ornon-naturally-occurring. In certain embodiments, the blockingoligonucleotides include one or more non-naturally-occurring nucleotideto, for example, increase melting temperature. Exemplary non-naturallyoccurring oligonucleotides include modified DNA or RNA nucleotides. Anexemplary modified RNA nucleotide is a locked nucleic acid (LNA),wherein the ribose moiety of an LNA nucleotide is modified with an extrabridge connecting the 2′ oxygen and 4′ carbon (Kaur, H; Arora, A;Wengel, J; Maiti, S; Arora, A.; Wengel, J.; Maiti, S. (2006).“Thermodynamic, Counterion, and Hydration Effects for the Incorporationof Locked Nucleic Acid Nucleotides into DNA Duplexes”. Biochemistry 45(23): 7347-55). Other modified exemplary DNA and RNA nucleotidesinclude, but are not limited to, peptide nucleic acid (PNA) composed ofrepeating N-(2-aminoethyl)-glycine units linked by peptide bonds(Egholm, M. et al. (1993) Nature 365 (6446): 566-8); a DNA or RNAoligonucleotide modified to capture low GC regions; a bicyclic nucleicacid (BNA) or a crosslinked oligonucleotide; a modified 5-methyldeoxycytidine; and 2,6-diaminopurine. Other modified DNA and RNAnucleotides are known in the art.

Design and Construction of Baits

A bait can be a nucleic acid molecule, for example, a DNA or RNAmolecule, which can hybridize to (for example, be complementary to), andthereby allow capture of a target nucleic acid. In one embodiment, abait is an RNA molecule. In other embodiments, a bait includes a bindingentity, for example, an affinity tag, that allows capture andseparation, for example, by binding to a binding entity, of a hybridformed by a bait and a nucleic acid hybridized to the bait. In oneembodiment, a bait is suitable for solution phase hybridization.

Typically, RNA molecules are used as bait sequences. A RNA-DNA duplex ismore stable than a DNA-DNA duplex, and therefore provides forpotentially better capture of nucleic acids.

RNA baits can be made as described elsewhere herein, using methods knownin the art including, but not limited to, de novo chemical synthesis andtranscription of DNA molecules using a DNA-dependent RNA polymerase. Inone embodiment, the bait sequence is produced using known nucleic acidamplification methods, such as PCR, for example, using human DNA orpooled human DNA samples as the template. The oligonucleotides can thenbe converted to RNA baits. In one embodiment, in vitro transcription isused, for example, based on adding an RNA polymerase promoter sequenceto one end of the oligonucleotide. In one embodiment, the RNA polymerasepromoter sequence is added at the end of the bait by amplifying orreamplifying the bait sequence, for example, using PCR or other nucleicacid amplification methods, for example, by tailing one primer of eachtarget-specific primer pairs with an RNA promoter sequence. In oneembodiment, the RNA polymerase is a T7 polymerase, a SP6 polymerase, ora T3 polymerase. In one embodiment, RNA bait is labeled with a tag, forexample, an affinity tag. In one embodiment, RNA bait is made by invitro transcription, for example, using biotinylated UTP. In anotherembodiment, RNA bait is produced without biotin and then biotin iscrosslinked to the RNA molecule using methods well known in the art,such as psoralen crosslinking. In one embodiment, the RNA bait is anRNase-resistant RNA molecule, which can be made, for example, by usingmodified nucleotides during transcription to produce RNA molecule thatresists RNase degradation. In one embodiment, the RNA bait correspondsto only one strand of the double-stranded DNA target. Typically, suchRNA baits are not self-complementary and are more effective ashybridization drivers.

The bait sets can be designed from reference sequences, such that thebaits are optimal for selecting targets of the reference sequences. Insome embodiments, bait sequences are designed using a mixed base (forexample, degeneracy). For example, the mixed base(s) can be included inthe bait sequence at the position(s) of a common SNP or mutation, tooptimize the bait sequences to catch both alleles (for example, SNP andnon-SNP; mutant and non-mutant). In some embodiments, all known sequencevariations (or a subset thereof) can be targeted with multipleoligonucleotide baits, rather than by using mixed degenerateoligonucleotides.

In certain embodiments, the bait set includes an oligonucleotide (or aplurality of oligonucleotides) between about 100 nucleotides and 300nucleotides in length. Typically, the bait set includes anoligonucleotide (or a plurality of oligonucleotides) between about 130nucleotides and 230 nucleotides, or about 150 and 200 nucleotides, inlength. In other embodiments, the bait set includes an oligonucleotide(or a plurality of oligonucleotides) between about 300 nucleotides and1000 nucleotides in length.

In some embodiments, the target member-specific sequences in theoligonucleotide is between about 40 and 1000 nucleotides, about 70 and300 nucleotides, about 100 and 200 nucleotides in length, typicallybetween about 120 and 170 nucleotides in length.

In some embodiments, the bait set includes a binding entity. The bindingentity can be an affinity tag on each bait sequence. In someembodiments, the affinity tag is a biotin molecule or a hapten. Incertain embodiments, the binding entity allows for separation of thebait/member hybrids from the hybridization mixture by binding to apartner, such as an avidin molecule, or an antibody that binds to thehapten or an antigen-binding fragment thereof.

In other embodiments, the oligonucleotides in the bait set containsforward and reverse complemented sequences for the same target membersequence whereby the oligonucleotides with reverse-complementedmember-specific sequences also carry reverse complemented universaltails. This can lead to RNA transcripts that are the same strand, thatis, not complementary to each other.

In other embodiments, the bait set includes oligonucleotides thatcontain degenerate or mixed bases at one or more positions. In stillother embodiments, the bait set includes multiple or substantially allknown sequence variants present in a population of a single species orcommunity of organisms. In one embodiment, the bait set includesmultiple or substantially all known sequence variants present in a humanpopulation.

In other embodiments, the bait set includes cDNA sequences or is derivedfrom cDNAs sequences. In other embodiments, the bait set includesamplification products (for example, PCR products) that are amplifiedfrom genomic DNA, cDNA or cloned DNA.

In other embodiments, the bait set includes RNA molecules. In someembodiments, the set includes chemically, enzymatically modified, or invitro transcribed RNA molecules, including but not limited to, thosethat are more stable and resistant to RNase.

In yet other embodiments, the baits are produced by methods described inUS 2010/0029498 and Gnirke, A. et al. (2009) Nat Biotechnol.27(2):182-189, incorporated herein by reference. For example,biotinylated RNA baits can be produced by obtaining a pool of syntheticlong oligonucleotides, originally synthesized on a microarray, andamplifying the oligonucleotides to produce the bait sequences. In someembodiments, the baits are produced by adding an RNA polymerase promotersequence at one end of the bait sequences, and synthesizing RNAsequences using RNA polymerase. In one embodiment, libraries ofsynthetic oligodeoxynucleotides can be obtained from commercialsuppliers, such as Agilent Technologies, Inc., and amplified using knownnucleic acid amplification methods.

Accordingly, a method of making the aforesaid bait set is provided. Themethod includes selecting one or more target specific baitoligonucleotide sequences (for example, one or more mutation capturing,reference or control oligonucleotide sequences as described herein);obtaining a pool of target specific bait oligonucleotide sequences (forexample, synthesizing the pool of target specific bait oligonucleotidesequences, for example, by microarray synthesis); and optionally,amplifying the oligonucleotides to produce the bait set.

In other embodiments, the methods further include amplifying (forexample, by PCR) the oligonucleotides using one or more biotinylatedprimers. In some embodiments, the oligonucleotides include a universalsequence at the end of each oligonucleotide attached to the microarray.The methods can further include removing the universal sequences fromthe oligonucleotides. Such methods can also include removing thecomplementary strand of the oligonucleotides, annealing theoligonucleotides, and extending the oligonucleotides. In some of theseembodiments, the methods for amplifying (for example, by PCR) theoligonucleotides use one or more biotinylated primers. In someembodiments, the method further includes size selecting the amplifiedoligonucleotides.

In one embodiment, an RNA bait set is made. The methods includeproducing a set of bait sequences according to the methods describedherein, adding a RNA polymerase promoter sequence at one end of the baitsequences, and synthesizing RNA sequences using RNA polymerase. The RNApolymerase can be chosen from a T7 RNA polymerase, an SP6 RNA polymeraseor a T3 RNA polymerase. In other embodiments, the RNA polymerasepromoter sequence is added at the ends of the bait sequences byamplifying (for example, by PCR) the bait sequences. In embodimentswhere the bait sequences are amplified by PCR with specific primer pairsout of genomic or cDNA, adding an RNA promoter sequence to the 5′ end ofone of the two specific primers in each pair will lead to a PCR productthat can be transcribed into a RNA bait using standard methods.

In other embodiments, bait sets can be produced using human DNA orpooled human DNA samples as the template. In such embodiments, theoligonucleotides are amplified by polymerase chain reaction (PCR). Inother embodiments, the amplified oligonucleotides are reamplified byrolling circle amplification or hyperbranched rolling circleamplification. The same methods also can be used to produce baitsequences using human DNA or pooled human DNA samples as the template.The same methods can also be used to produce bait sequences usingsubfractions of a genome obtained by other methods, including but notlimited to restriction digestion, pulsed-field gel electrophoresis,flow-sorting, CsCl density gradient centrifugation, selective kineticreassociation, microdissection of chromosome preparations and otherfractionation methods known to those skilled in the art.

In certain embodiments, the number of baits in the bait set is less than1,000. In other embodiments, the number of baits in the bait set isgreater than 1,000, greater than 5,000, greater than 10,000, greaterthan 20,000, greater than 50,000, greater than 100,000, or greater than500,000.

The length of the bait sequence can be between about 70 nucleotides and1000 nucleotides. In one embodiment, the bait length is between about100 and 300 nucleotides, 110 and 200 nucleotides, or 120 and 170nucleotides, in length. In addition to those mentioned above,intermediate oligonucleotide lengths of about 70, 80, 90, 100, 110, 120,130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 300,400, 500, 600, 700, 800, and 900 nucleotides in length can be used inthe methods described herein. In some embodiments, oligonucleotides ofabout 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200,210, 220, or 230 bases can be used.

Each bait sequence can include a target-specific (for example, amember-specific) bait sequence and universal tails on one or both ends.As used herein, the term “bait sequence” can refer to thetarget-specific bait sequence or the entire oligonucleotide includingthe target-specific “bait sequence” and other nucleotides of theoligonucleotide. The target-specific sequences in the baits are betweenabout 40 nucleotides and 1000 nucleotides in length. In one embodiment,the target-specific sequence is between about 70 nucleotides and 300nucleotides in length. In another embodiment, the target-specificsequence is between about 100 nucleotides and 200 nucleotides in length.In yet another embodiment, the target-specific sequence is between about120 nucleotides and 170 nucleotides in length, typically 120 nucleotidesin length. Intermediate lengths in addition to those mentioned abovealso can be used in the methods described herein, such astarget-specific sequences of about 40, 50, 60, 70, 80, 90, 100, 110,120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250,300, 400, 500, 600, 700, 800, and 900 nucleotides in length, as well astarget-specific sequences of lengths between the above-mentionedlengths.

In one embodiment, the bait is an oligomer (for example, comprised ofRNA oligomers, DNA oligomers, or a combination thereof) about 50 to 200nucleotides in length (for example, about 50, 60, 80, 90, 100, 110, 120,130, 140, 150, 160, 170, 190, or 200 nucleotides in length). In oneembodiment, each bait oligomer includes about 120 to 170, or typically,about 120 nucleotides, which are a target specific bait sequence. Thebait can comprise additional non-target specific nucleotide sequences atone or both ends. The additional nucleotide sequences can be used, forexample, for PCT amplification or as a bait identifier. In certainembodiments, the bait additionally comprises a binding entity asdescribed herein (for example, a capture tag such as a biotin molecule).The binding entity, for example, biotin molecule, can be attached to thebait, for example, at the 5′-, 3′-end, or internally (for example, byincorporating a biotinylated nucleotide), of the bait. In oneembodiment, the biotin molecule is attached at the 5′-end of the bait.

In one exemplary embodiment, the bait is an oligonucleotide about 150nucleotides in length, of which 120 nucleotides are target-specific“bait sequence”. The other 30 nucleotides (for example, 15 nucleotideson each end) are universal arbitrary tails used for PCR amplification.The tails can be any sequence selected by the user. For example, thepool of synthetic oligonucleotides can include oligonucleotides of thesequence of 5′-ATCGCACCAGCGTGTN₁₂₀CACTGCGGCTCCTCA-3′ (SEQ ID NO:81) withN₁₂₀ indicating the target-specific bait sequences.

The bait sequences described herein can be used for selection of exonsand short target sequences. In one embodiment, the bait is between about100 nucleotides and 300 nucleotides in length. In another embodiment,the bait is between about 130 nucleotides and 230 nucleotides in length.In yet another embodiment, the bait is between about 150 nucleotides and200 nucleotides in length. The target-specific sequences in the baits,for example, for selection of exons and short target sequences, arebetween about 40 nucleotides and 1000 nucleotides in length. In oneembodiment, the target-specific sequence is between about 70 nucleotidesand 300 nucleotides in length. In another embodiment, thetarget-specific sequence is between about 100 nucleotides and 200nucleotides in length. In yet another embodiment, the target-specificsequence is between about 120 nucleotides and 170 nucleotides in length.

In some embodiments, long oligonucleotides can minimize the number ofoligonucleotides necessary to capture the target sequences. For example,one oligonucleotide can be used per exon. It is known in the art thatthe mean and median lengths of the protein-coding exons in the humangenome are about 164 and 120 base pairs, respective. Longer baits can bemore specific and capture better than shorter ones. As a result, thesuccess rate per oligonucleotide bait sequence is higher than with shortoligonucleotides. In one embodiment, the minimum bait-covered sequenceis the size of one bait (for example, 120-170 bases), for example, forcapturing exon-sized targets. In determining the length of the baitsequences, one also can take into consideration that unnecessarily longbaits catch more unwanted DNA directly adjacent to the target. Longeroligonucleotide baits can also be more tolerant to polymorphisms in thetargeted region in the DNA samples than shorter ones. Typically, thebait sequences are derived from a reference genome sequence. If thetarget sequence in the actual DNA sample deviates from the referencesequence, for example if it contains a single-nucleotide polymorphism(SNP), it can hybridize less efficiently to the bait and may thereforebe under-represented or completely absent in the sequences hybridized tothe bait sequences. Allelic drop-outs due to SNPs can be less likelywith the longer synthetic baits molecules for the reason that a singlemispair in, for example, 120 to 170 bases can have less of an effect onhybrid stability than a single mismatch in, 20 or 70 bases, which arethe typical bait or primer lengths in multiplex amplification andmicroarray capture, respectively.

For selection of targets that are long compared to the length of thecapture baits, such as genomic regions, bait sequence lengths aretypically in the same size range as the baits for short targetsmentioned above, except that there is no need to limit the maximum sizeof bait sequences for the sole purpose of minimizing targeting ofadjacent sequences. Alternatively, oligonucleotides can be titled acrossa much wider window (typically 600 bases). This method can be used tocapture DNA fragments that are much larger (for example, about 500bases) than a typical exon. As a result, much more unwanted flankingnon-target sequences are selected.

Bait Synthesis

The baits can be any type of oligonucleotide, for example, DNA or RNA.The DNA or RNA baits (“oligo baits”) can be synthesized individually, orcan be synthesized in an array, as a DNA or RNA bait set (“arraybaits”). An oligo bait, whether provided in an array format, or as anisolated oligo, is typically single stranded. The bait can additionallycomprise a binding entity as described herein (for example, a capturetag such as a biotin molecule). The binding entity, for example, biotinmolecule, can be attached to the bait, for example, at the 5′ or 3′-endof the bait, typically, at the 5′-end of the bait.

In some embodiments, individual oligo baits can be added to an arraybait set. In these cases, the oligo baits can be designed to target thesame areas as those targeted by the array baits, and additional oligobaits can be designed and added to the standard array baits to achieveenhanced, or more thorough, coverage in certain areas of the genome. Forexample, additional oligo baits can be designed to target areas of poorsequencing coverage following an initial sequencing round with astandard array bait set. In some embodiments, the oligo baits aredesigned to have a tiled effect over the area of coverage for the arraybait set, or a tiled effect over the area of coverage for other oligobaits.

In one embodiment, the individual oligo baits are DNA oligos that areused to supplement an RNA or DNA oligo array bait set, or a combinationthereof (for example, a commercially available array bait set). In otherembodiments, individual oligo baits are DNA oligos that are used tosupplement an RNA or DNA oligo bait set, or a combination thereof, thatis a collection of individually designed and synthesized oligos. In oneembodiment, the individual oligo baits are RNA oligos that are used tosupplement an RNA or DNA oligo array bait set, or a combination thereof(for example, a commercially available array bait set). In otherembodiments individual oligo baits are RNA oligos that are used tosupplement an RNA or DNA oligo bait set, or a combination thereof, thatis a collection of individually designed and synthesized oligos.

In yet another embodiment, the individual oligo baits are DNA oligosthat are used to supplement a DNA oligo array bait set (for example, acommercially available array bait set), and in other embodimentsindividual oligo baits are DNA oligos that are used to supplement a DNAoligo bait set that is a collection of individually designed andsynthesized oligos.

In yet another embodiment, the individual oligo baits are DNA oligosthat are used to supplement a RNA oligo array bait set (for example, acommercially available array bait set), and in other embodimentsindividual oligo baits are DNA oligos that are used to supplement a RNAoligo bait set that is a collection of individually designed andsynthesized oligos.

In yet another embodiment, the individual oligo baits are RNA oligosthat are used to supplement a RNA oligo array bait set (for example, acommercially available array bait set), and in other embodimentsindividual oligo baits are RNA oligos that are used to supplement a RNAoligo bait set that is a collection of individually designed andsynthesized oligos.

In yet another embodiment, the individual oligo baits are RNA oligosthat are used to supplement a DNA oligo array bait set (for example, acommercially available array bait set), and in other embodimentsindividual oligo baits are RNA oligos that are used to supplement a DNAoligo bait set that is a collection of individually designed andsynthesized oligos.

In one embodiment, oligo baits are designed to target sequences in genesof particular interest, such as to achieve increased sequencing coverageof expanded gene sets.

In another embodiment, oligo baits are designed to target sequencesrepresenting a subset of the genome, and are mixed and used as a poolinstead of, or in addition to, array baits.

In one embodiment, a first set of oligo baits is designed to targetareas of poor sequencing coverage, and a second set of oligo baits isdesigned to target genes of particular interest. Then both sets of oligobaits are combined and, optionally, mixed with a standard array bait setto be used for sequencing.

In one embodiment, an oligo bait mix is used, for example, tosimultaneously sequence targeted gene panels and to screen a panel ofsingle nucleotide polymorphisms (SNPs) created, such as for the purposeof looking for genomic rearrangements and copy number alterations(equivalent of arrayed CGH (Comparative Genomic Hybridization)). Forexample, a panel of SNPs can first be created by the array method asarray baits, and then additional DNA oligonucleotide baits can bedesigned to target areas of poor sequencing coverage to a targeted setof genes. Sequencing of the collection of SNPs can then be repeated withthe original array bait set plus the additional oligo baits to achievetotal intended sequencing coverage.

In some embodiments, oligo baits are added to a standard array bait setto achieve more thorough sequencing coverage. In one embodiment, oligobaits are designed to target areas of poor sequencing coverage followingan initial sequencing round with a standard array bait set.

In another embodiment, oligo baits are designed to target sequences ingenes of particular interest. These oligo baits can be added to astandard array bait set or to existing oligo/array hybrid bait sets toachieve, for example, increased sequencing coverage of expanded genesets without going through an entire array bait pool re-design cycle.

Oligo baits can be obtained from a commercial source, such as NimbleGen(Roche) or Integrated DNA Technologies (IDT) for DNA oligos. Oligos canalso be obtained from Agilent Technologies. Protocols for enrichment arepublicly available, for example, SureSelect Target.

Enrichment System.

Baits can be produced by methods described in US 2010/0029498 andGnirke, A. et al. (2009) Nat Biotechnol. 27(2):182-189, incorporatedherein by reference. For example, biotinylated RNA baits can be producedby obtaining a pool of synthetic long oligonucleotides, originallysynthesized on a microarray, and amplifying the oligonucleotides toproduce the bait sequences. In some embodiments, the baits are producedby adding an RNA polymerase promoter sequence at one end of the baitsequences, and synthesizing RNA sequences using RNA polymerase. In oneembodiment, libraries of synthetic oligodeoxynucleotides can be obtainedfrom commercial suppliers, such as Agilent Technologies, Inc., andamplified using known nucleic acid amplification methods.

For example, a large collection of baits can be generated from a custompool of synthetic oligonucleotides originally synthesized on anoligonucleotide array, for example, an Agilent programmable DNAmicroarray. Accordingly, at least about 2,500, 5,000, 10,000, 20,000,3,000, 40,000, 50,000, or 60,000 unique oligonucleotides can besynthesized simultaneously.

In one embodiment, a minimal set of unique oligonucleotides are chosenand additional copies (for example, alternating between reversecomplements and the original forward strands) are added until themaximum capacity of the synthetic oligonucleotide array has beenreached, for example, for baits designed to capture a pre-selected setof targets (for example, pre-selected set of exons). In anotherembodiment, the target is represented at least twice, for example, bysynthesizing both forward and reverse-complemented oligonucleotides.Synthesizing forward and reverse-complemented oligonucleotides for agiven target can provide better redundancy at the synthesis step thansynthesizing the very same sequence twice. In yet another embodiment,the PCR product or bait is the same for forward and reverse-complementedoligonucleotides.

The oligonucleotides from the chips are synthesized once, and then canbe amplified to create a set of oligonucleotides that can be used manytimes. This approach generates a universal reagent that can be used asbait for a large number of selection experiments, thereby amortizing thechip cost to be a small fraction of the sequencing cost. Alternatively,bait sequences can be produced using known nucleic acid amplificationmethods, such as PCR, using human DNA or pooled human DNA samples as thetemplate.

Following synthesis, the oligonucleotides can be liberated (for example,stripped) from the array by chemical cleavage followed by removal of theprotection groups and PCR amplified into double-stranded DNA usinguniversal primers. A second round of PCR can be used to incorporate apromoter (for example, T7, SP6, or T3 promoter) site into the amplicon,which is used to transcribe the DNA into single-stranded RNA.

In one embodiment, the baits are tiled along the sequences (for example,exons) without gaps or overlaps. For example, the baits can start at the“left”-most coding base in the strand of the reference genome sequenceshown in the UCSC genome browser (for example, 5′ to 3′ or 3′ to 5′along the coding sequence, depending on the orientation of the gene) andadditional baits are added until all coding bases are covered. Inanother embodiment, at least two, three, four, or five baits for eachtarget are designed, overlapping by at least about 15, 30, 45, or 60bases. After oligonucleotide synthesis and PCR amplification usinguniversal primers, one of the tails of the double-stranded DNA can beenzymatically followed by the degradation of one of the strands. Thesingle-stranded products can be hybridized, made fully double strandedby filling in, and amplified by PCR. In this manner, it is possible toproduce baits that contain at least about 300, 400, 500, or 600contiguous target-specific bases which is more than can be chemicallysynthesized. Such long baits can be useful for applications that requirehigh specificity and sensitivity, or for applications that do notnecessarily benefit from limiting the length of the baits (for example,capture of long contiguous genomic regions).

In one embodiment, the coverage of each target can be assessed andtargets that yield similar coverage can be grouped. Distinct sets ofbait sequences can be created for each group of targets, furtherimproving the representation. In another embodiment, oligonucleotidesfrom microarray chips are tested for efficacy of hybridization, and aproduction round of microarray chips ordered on which oligonucleotidesare grouped by their capture efficacy, thus compensating for variationin bait efficacy. In yet another embodiment, oligonucleotide pools canbe aggregated to form a relatively small number of composite pools, suchthat there is little variation in capture efficacy among them.

The baits described herein can be labeled with a tag, for example, anaffinity tag. Exemplary affinity tags include, but not limited to,biotin molecules, magnetic particles, haptens, or other tag moleculesthat permit isolation of baits tagged with the tag molecule. Suchmolecules and methods of attaching them to nucleic acids (for example,the baits used in the methods disclosed herein) are well known in theart. Exemplary methods for making biotinylated baits are described, forexample, in Gnirke A. et al., Nat. Biotechnol. 2009; 27(2):182-9, whichis incorporated herein by reference in entirety.

Also known in the art are molecules, particles or devices that bind toor are capable of separating the set of tagged baits from thehybridization mixture. In one embodiment, the molecule, particle, ordevice binds to the tag (for example, the affinity tag). In oneembodiment, the molecule, particle, or device is an avidin molecule, amagnet, or an antibody or antigen-binding fragment thereof. In oneembodiment, the tagged baits are separated using a magnetic bead coatedwith streptavidin molecules.

Exemplary methods to prepare oligonucleotide libraries are described,for example, in Gnirke A. et al., Nat. Biotechnol. 2009; 27(2):182-9,and Blumenstiel B. et al., Curr. Protoc. Hum. Genet. 2010; Chapter 18:Unit 18.4, which are incorporated herein by reference in entirety.

The methods and compositions featured in the invention involve tuningthe relative sequence coverage of each bait set/target category. Methodsfor implementing differences in relative sequence coverage in baitdesign include one or more of:

-   -   (i) Differential representation of different bait sets—The bait        set design to capture a given target (for example, a target        member) can be included in more/fewer number of copies to        enhance/reduce relative target coverage depths;    -   (ii) Differential overlap of bait subsets—The bait set design to        capture a given target (for example, a target member) can        include a longer or shorter overlap between neighboring baits to        enhance/reduce relative target coverage depths;    -   (iii) Differential bait parameters—The bait set design to        capture a given target (for example, a target member) can        include sequence modifications/shorter length to reduce capture        efficiency and lower the relative target coverage depths;    -   (iv) Mixing of different bait sets—Bait sets that are designed        to capture different target sets can be mixed at different molar        ratios to enhance/reduce relative target coverage depths;    -   (v) Using different types of oligonucleotide bait sets—In        certain embodiments, the bait set can include:        -   (a) one or more chemically (for example, non-enzymatically)            synthesized (for example, individually synthesized) baits,        -   (b) one or more baits synthesized in an array,        -   (c) one or more enzymatically prepared, for example, in            vitro transcribed, baits;        -   (d) any combination of (a), (b) and/or (c),        -   (e) one or more DNA oligonucleotides (for example, a            naturally or non-naturally occurring DNA oligonucleotide),        -   (f) one or more RNA oligonucleotides (for example, a            naturally or non-naturally occurring RNA oligonucleotide),        -   (g) a combination of (e) and (f), or        -   (h) a combination of any of the above.

The different oligonucleotide combinations can be mixed at differentratios, for example, a ratio chosen from 1:1, 1:2, 1:3, 1:4, 1:5, 1:10,1:20, 1:50; 1:100, 1:1000, or the like. In one embodiment, the ratio ofchemically-synthesized bait to array-generated bait is chosen from 1:5,1:10, or 1:20. The DNA or RNA oligonucleotides can be naturally- ornon-naturally-occurring. In certain embodiments, the baits include oneor more non-naturally-occurring nucleotide to, for example, increasemelting temperature. Exemplary non-naturally occurring oligonucleotidesinclude modified DNA or RNA nucleotides. An exemplary modified RNAnucleotide is a locked nucleic acid (LNA), wherein the ribose moiety ofan LNA nucleotide is modified with an extra bridge connecting the 2′oxygen and 4′ carbon (Kaur, H; Arora, A; Wengel, J; Maiti, S; Arora, A.;Wengel, J.; Maiti, S. (2006). “Thermodynamic, Counterion, and HydrationEffects for the Incorporation of Locked Nucleic Acid Nucleotides intoDNA Duplexes”. Biochemistry 45 (23): 7347-55). Other modified exemplaryDNA and RNA nucleotides include, but are not limited to, peptide nucleicacid (PNA) composed of repeating N-(2-aminoethyl)-glycine units linkedby peptide bonds (Egholm, M. et al. (1993) Nature 365 (6446): 566-8); aDNA or RNA oligonucleotide modified to capture low GC regions; abicyclic nucleic acid (BNA) or a crosslinked oligonucleotide; a modified5-methyl deoxycytidine; and 2,6-diaminopurine. Other modified DNA andRNA nucleotides are known in the art.

In certain embodiments, a substantially uniform or homogeneous coverageof a target sequence (for example, a target member) is obtained. Forexample, within each bait set/target category, uniformity of coveragecan be optimized by modifying bait parameters, for example, by one ormore of:

-   -   (i) Increasing/decreasing bait representation or overlap can be        used to enhance/reduce coverage of targets (for example, target        members), which are under/over-covered relative to other targets        in the same category;    -   (ii) For low coverage, hard to capture target sequences (for        example, high GC content sequences), expand the region being        targeted with the bait sets to cover, for example, adjacent        sequences (for example, less GC-rich adjacent sequences);    -   (iii) Modifying a bait sequence can be made to reduce secondary        structure of the bait and enhance its efficiency of selection;    -   (iv) Modifying a bait length can be used to equalize melting        hybridization kinetics of different baits within the same        category. Bait length can be modified directly (by producing        baits with varying lengths) or indirectly (by producing baits of        consistent length, and replacing the bait ends with arbitrary        sequence);    -   (v) Modifying baits of different orientation for the same target        region (that is, forward and reverse strand) may have different        binding efficiencies. The bait set with either orientation        providing optimal coverage for each target may be selected;    -   (vi) Modifying the amount of a binding entity, for example, a        capture tag (for example, biotin), present on each bait may        affect its binding efficiency. Increasing/decreasing the tag        level of baits targeting a specific target may be used to        enhance/reduce the relative target coverage;    -   (vii) Modifying the type of nucleotide used for different baits        can be altered to affect binding affinity to the target, and        enhance/reduce the relative target coverage; or    -   (viii) Using modified oligonucleotide baits, for example, having        more stable base pairing, can be used to equalize melting        hybridization kinetics between areas of low or normal GC content        relative to high GC content.

For example, different types of oligonucleotide bait sets can be used.

In one embodiment, the value for efficiency of selection is modified byusing different types of bait oligonucleotides to encompass pre-selectedtarget regions. For example, a first bait set (for example, anarray-based bait set comprising 10,000-50,000 RNA or DNA baits) can beused to cover a large target area (for example, 1-2 MB total targetarea). The first bait set can be spiked with a second bait set (forexample, individually synthesized RNA or DNA bait set comprising lessthan 5,000 baits) to cover a pre-selected target region (for example,selected subgenomic intervals of interest spanning, for example, 250 kbor less, of a target area) and/or regions of higher secondary structure,for example, higher GC content. Selected subgenomic intervals ofinterest may correspond to one or more of the genes or gene productsdescribed herein, or a fragment thereof. The second bait set may includeabout 2,000-5,000 baits depending on the bait overlap desired. In yetother embodiments, the second bait set can include selected oligo baits(for example, less than 400, 200, 100, 50, 40, 30, 20, 10 baits) spikedinto the first bait set. The second bait set can be mixed at any ratioof individual oligo baits. For example, the second bait set can includeindividual baits present as a 1:1 equimolar ratio. Alternatively, thesecond bait set can include individual baits present at different ratio(for example, 1:5, 1:10, 1:20), for example, to optimize capture ofcertain targets (for example, certain targets can have a 5-10× of thesecond bait compared to other targets).

Hybridization Conditions

The methods featured in the invention include the step of contacting thelibrary (for example, the nucleic acid library) with a plurality ofbaits to provide a selected library catch. The contacting step can beeffected in solution hybridization. In certain embodiments, the methodincludes repeating the hybridization step by one or more additionalrounds of solution hybridization. In some embodiments, the methodsfurther include subjecting the library catch to one or more additionalrounds of solution hybridization with the same or different collectionof baits.

In other embodiments, the methods featured in the invention furtherinclude amplifying the library catch (for example, by PCR). In otherembodiments, the library catch is not amplified.

In yet other embodiments, the methods further include the step ofsubjecting the library catch to genotyping, thereby identifying thegenotype of the selected nucleic acids.

More specifically, a mixture of several thousand bait sequences caneffectively hybridize to complementary nucleic acids in a group ofnucleic acids and that such hybridized nucleic acids (the subgroup ofnucleic acids) can be effectively separated and recovered. In oneembodiment, the methods described herein use a set of bait sequencescontaining more than about 1,000 bait sequences, more than about 2,000bait sequences, more than about 3,000 bait sequences, more than about4,000 bait sequences, more than about 5,000 bait sequences, more thanabout 6,000 bait sequences, more than about 7,000 bait sequences, morethan about 8,000 bait sequences, more than about 9,000 bait sequences,more than about 10,000 bait sequences, more than about 15,000 baitsequences, more than about 20,000 bait sequences, more than about 30,000bait sequences, more than about 40,000 bait sequences, or more thanabout 50,000 bait sequences.

In some embodiments, the selection process is repeated on the selectedsubgroup of nucleic acids, for example, in order to increase theenrichment of selected nucleic acids. For example, after one round ofhybridization, a several thousand fold enrichment of nucleic acids canbe observed. After a second round, the enrichment can rise, for example,to about 15,000-fold average enrichment, which can provide hundreds-foldcoverage of the target in a single sequencer run. Thus, for experimentsthat require enrichment factors not achievable in a single round ofhybrid selection, the methods typically include subjecting the isolatedsubgroup of nucleic acids (that is, a portion or all of the targetsequences) to one or more additional rounds of solution hybridizationwith the set of bait sequences.

Sequential hybrid selection with two different bait sequences (bait 1,bait 2) can be used to isolate and sequence the “intersection”, that is,the subgroup of DNA sequences that binds to bait 1 and to bait 2, forexample, used for applications that include but are not limited toenriching for inter-chromosomal. For example, selection of DNA from atumor sample with a bait specific for sequences on chromosome 1 followedby selection from the product of the first selection of sequences thathybridize to a bait specific for chromosome 2 may enrich for sequencesat chromosomal translocation junctions that contain sequences from bothchromosomes.

The molarity of the selected subgroup of nucleic acids can be controlledsuch that the molarity of any particular nucleic acid is within a smallvariation of the average molarity of all selected nucleic acids in thesubgroup of nucleic acids. Methods for controlling and optimizing theevenness of target representation include, but are not limited to,rational design of bait sequences based on physicochemical as well asempirical rules of probe design well known in the art, and pools ofbaits where sequences known or suspected to underperform areoverrepresented to compensate for their intrinsic weaknesses. In someembodiments, at least about 50%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or95% of the isolated subgroup of nucleic acids is within about 20-fold,15-fold, 10-fold, 5-fold, 3-fold, or 2-fold of the mean molarity. In oneembodiment, at least about 50% of the isolated subgroup of nucleic acidsis within about 3-fold of the mean molarity. In another embodiment, atleast about 90% of the isolated subgroup of nucleic acids is withinabout 10-fold of the mean molarity.

Variations in efficiency of selection can be further adjusted byaltering the concentration of the baits. In one embodiment, theefficiency of selection is adjusted by leveling the efficiency ofindividual baits within a group (for example, a first, second or thirdplurality of baits) by adjusting the relative abundance of the baits, orthe density of the binding entity (for example, the hapten or affinitytag density) in reference to differential sequence capture efficiencyobserved when using an equimolar mix of baits, and then introducing adifferential excess as much of internally-leveled group 1 to the overallbait mix relative to internally-leveled group 2.

In certain embodiments, the methods described herein can achieve an evencoverage of the target sequences. In one embodiment, the percent oftarget bases having at least about 50% of the expected coverage is atleast about 60%, 70%, 80%, or 90%, for example, for short targets suchas protein-coding exons. In another embodiment, the percent of targetbases having at least about 50% of the expected coverage is at leastabout 80%, 90%, or 95%, for example, for targets that are long comparedto the length of the capture baits, such as genomic regions.

Prior to hybridization, baits can be denatured according to methods wellknown in the art. In general, hybridization steps comprise adding anexcess of blocking DNA to the labeled bait composition, contacting theblocked bait composition under hybridizing conditions with the targetsequences to be detected, washing away unhybridized baits, and detectingthe binding of the bait composition to the target.

Baits are hybridized or annealed to the target sequences underhybridizing conditions. “Hybridizing conditions” are conditions thatfacilitate annealing between a bait and target nucleic acid. Sinceannealing of different baits will vary depending on probe length, baseconcentration and the like, annealing is facilitated by varying baitconcentration, hybridization temperature, salt concentration and otherfactors well known in the art.

Hybridization conditions are facilitated by varying the concentrations,base compositions, complexities, and lengths of the baits, as well assalt concentrations, temperatures, and length of incubation. Forexample, hybridizations can be performed in hybridization buffercontaining 5×SSPE, 5×Denhardt's, 5 mM EDTA and 0.1% SDS and blocking DNAto suppress non-specific hybridization. RNase inhibitors can be used ifthe bait is RNA. In general, hybridization conditions, as describedabove, include temperatures of about 25° C. to about 65° C., typicallyabout 65° C., and incubation lengths of about 0.5 hours to about 96hours, typically about 66 hours. Additional exemplary hybridizationconditions are in Example 12A-12C and Table 14 herein.

The methods described herein are adaptable to standard liquid handlingmethods and devices. In some embodiments, the method is carried outusing automated liquid handling technology as is known in the art, suchas devices that handle multiwell plates (see for example, Gnirke, A. etal. (2009) Nat Biotechnol. 27(2):182-189). This can include, but notlimited to, automated library construction, and steps of solutionhybridization including set-up and post-solution hybridization washes.For example, an apparatus can be used for carrying out such automatedmethods for the bead-capture and washing steps after the solutionhybridization reaction. Exemplary apparatus can include, but not limitedto, the following positions: a position for a multi-well platecontaining streptavidin-coated magnetic beads, a position for themultiwall plate containing the solution hybrid-selection reactions, I/Ocontrolled heat blocks to preheat reagents and to carry out washingsteps at a user-defined temperature, a position for a rack of pipettips, a position with magnets laid out in certain configurations thatfacilitate separation of supernatants from magnet-immobilized beads, awashing station that washes pipet tips and disposed of waste, andpositions for other solutions and reagents such as low andhigh-stringency washing buffers or the solution for alkaline elution ofthe final catch. In one embodiment, the apparatus is designed to processup to 96 hybrid selections from the bead-capture step through the catchneutralization step in parallel. In another embodiment, one or morepositions have a dual function. In yet another embodiment, the user isprompted by the protocol to exchange one plate for another.

The directly-selected nucleic acids can be concatenated and sheared,which is done to overcome the limitations of short sequencing reads. Inone embodiment, each exon-sized sequencing target is captured with asingle bait molecule that is about the same size as the target and hasendpoints near the endpoints of the target. Only hybrids that formdouble strand molecules having approximately 100 or more contiguous basepairs survive stringent post-hybridization washes. As a result, theselected subgroup of nucleic acids (that is, the “catch”) is enrichedfor randomly sheared genomic DNA fragments whose ends are near the endsof the bait molecules. Mere end-sequencing of the “catch” with veryshort sequencing reads can give higher coverage near the end (or evenoutside) of the target and lower coverage near the middle.

Concatenating “catch” molecules by ligation and followed by randomshearing and shotgun sequencing is one method to get sequence coveragealong the entire length of the target sequence. This method produceshigher percentage of sequenced bases that are on target (as opposed tonear target) than end sequencing with very short reads. Methods forconcatenating molecules by co-ligation are well known in the art.Concatenation can be performed by simple blunt end ligation. “Sticky”ends for efficient ligation can be produced by a variety of methodsincluding PCR amplification of the “catch” with PCR primers that haverestriction sites near their 5′ ends followed by digestion with thecorresponding restriction enzyme (for example, NotI) or by strategiessimilar to those commonly used for ligation-independent cloning of PCRproducts such as partial “chew-back” by T4 DNA polymerase (Aslanidis andde Jong, Nucleic Acids Res. 18:6069-6074, 1990) or treatment ofuracil-containing PCR products with UDG glycosylase and lyase endo VIII(for example, New England Biolabs cat. E5500S).

In another embodiment, a staggered set of bait molecules is used totarget a region, obtaining frequent bait ends throughout the targetregion. In some embodiments, merely end-sequenced “catch” (that is,without concatenation and shearing) provides fairly uniform sequencecoverage along the entire region that is covered by bait including theactual sequencing target (for example, an exon). As staggering the baitmolecules widens the segment covered by bait, the sequenced bases aredistributed over a wider area. As a result, the ratio of sequence ontarget to near target is lower than for selections with non-overlappingbaits that often require only a single bait per target.

In another embodiment, end sequencing with slightly longer reads (forexample, 76 bases) is the typical method for sequencing short selectedtargets (for example, exons). Unlike end sequencing with very shortreads, this method leads to a unimodal coverage profile without a dip incoverage in the middle. This method is easier to perform than theconcatenate and shear method described above, results in relatively evencoverage along the targets, and generates a high percentage of sequencedbases fall on bait and on target proper.

In one embodiment, the selected subgroup of nucleic acids are amplified(for example, by PCR) prior to being analyzed by sequencing orgenotyping. In another embodiment, the subgroup is analyzed without anamplification step, for example, when the selected subgroup is analyzedby sensitive analytical methods that can read single molecules.

Sequencing

The invention also includes methods of sequencing nucleic acids. Inthese methods, nucleic acid library members are isolated by using themethods described herein, for example, using solution hybridization,thereby providing a library catch. The library catch or a subgroupthereof can be sequenced. Accordingly, the methods featured in theinvention further include analyzing the library catch. In oneembodiment, the library catch is analyzed by a sequencing method, forexample, a next-generation sequencing method as described herein. Themethods include isolating a library catch by solution hybridization, andsubjecting the library catch by nucleic acid sequencing. In certainembodiments, the library catch can be re-sequenced.

Any method of sequencing known in the art can be used. Sequencing ofnucleic acids isolated by selection methods are typically carried outusing next-generation sequencing (NGS). Next-generation sequencingincludes any sequencing method that determines the nucleotide sequenceof either individual nucleic acid molecules or clonally expanded proxiesfor individual nucleic acid molecules in a highly parallel fashion (forexample, greater than 10⁵ molecules are sequenced simultaneously). Inone embodiment, the relative abundance of the nucleic acid species inthe library can be estimated by counting the relative number ofoccurrences of their cognate sequences in the data generated by thesequencing experiment. Next generation sequencing methods are known inthe art, and are described, for example, in Metzker, M. (2010) NatureBiotechnology Reviews 11:31-46, incorporated herein by reference.

In one embodiment, the next-generation sequencing allows for thedetermination of the nucleotide sequence of an individual nucleic acidmolecule (for example, Helicos BioSciences' HeliScope Gene Sequencingsystem, and Pacific Biosciences' PacBio RS system). In otherembodiments, the sequencing method determines the nucleotide sequence ofclonally expanded proxies for individual nucleic acid molecules (forexample, the Solexa sequencer, Illumina Inc., San Diego, Calif.; 454Life Sciences (Branford, Conn.), and Ion Torrent). for example,massively parallel short-read sequencing (for example, the Solexasequencer, Illumina Inc., San Diego, Calif.), which generates more basesof sequence per sequencing unit than other sequencing methods thatgenerate fewer but longer reads. Other methods or machines fornext-generation sequencing include, but not limited to, the sequencersprovided by 454 Life Sciences (Branford, Conn.), Applied Biosystems(Foster City, Calif.; SOLiD sequencer), Helicos BioSciences Corporation(Cambridge, Mass.), and emulsion and ° fluidic sequencing technologynanodroplets (for example, GnuBio droplets).

Platforms for next-generation sequencing include, but are not limitedto, Roche/454's Genome Sequencer (GS) FLX System, Illumina/Solexa'sGenome Analyzer (GA), Life/APG's Support Oligonucleotide LigationDetection (SOLiD) system, Polonator's G.007 system, Helicos BioSciences'HeliScope Gene Sequencing system, and Pacific Biosciences' PacBio RSsystem.

NGS technologies can include one or more of steps, for example, templatepreparation, sequencing and imaging, and data analysis.

Additional exemplary sequencing methodologies are known in the art, forexample, some of which are described in commonly owned, U.S. Ser. No.13/339,986 and PCT/US11/67725, both filed on Dec. 29, 2011, the contentsof which are incorporated by reference.

Alignment

Alignment is the process of matching a read with a location, forexample, a genomic location. Misalignment (for example, the placement ofbase-pairs from a short read on incorrect locations in the genome)., forexample, misalignment due to sequence context (for example, presence ofrepetitive sequence) of reads around an actual cancer mutation can leadto reduction in sensitivity of mutation detection, as reads of thealternate allele may be shifted off the main pile-up of alternate allelereads. If the problematic sequence context occurs where no actualmutation is present, mis-alignment may introduce artifactual reads of“mutated” alleles by placing actual reads of reference genome bases ontothe wrong location. Because mutation-calling algorithms for multipliedmultigene analysis should be sensitive to even low-abundance mutations,these misalignments may increase false positive discovery rates/reducespecificity.

As discussed herein, reduced sensitivity for actual mutations may beaddressed by evaluating the quality of alignments (manually or in anautomated fashion) around expected mutation sites in the genes beinganalyzed. The sites to be evaluated can be obtained from databases ofcancer mutations (for example, COSMIC). Regions that are identified asproblematic can be remedied with the use of an algorithm selected togive better performance in the relevant sequence context, for example,by alignment optimization (or re-alignment) using slower, but moreaccurate alignment algorithms such as Smith-Waterman alignment. In caseswhere general alignment algorithms cannot remedy the problem, customizedalignment approaches may be created by, for example: adjustment ofmaximum difference mismatch penalty parameters for genes with a highlikelihood of containing substitutions; adjusting specific mismatchpenalty parameters based on specific mutation types that are common incertain tumor types (for example, C→T in melanoma); or adjustingspecific mismatch penalty parameters based on specific mutation typesthat are common in certain sample types (for example, substitutions thatare common in FFPE).

Reduced specificity (increased false positive rate) in the evaluatedgene regions due to mis-alignment can be assessed by manual or automatedexamination of all mutation calls in samples sequenced. Those regionsfound to be prone to spurious mutation calls due to mis-alignment can besubjected to same alignment remedies as above. In cases where noalgorithmic remedy is found possible, “mutations” from the problemregions can be classified or screened out from the test panel.

Insertions/Deletions (Indels)

Generally, the accurate detection of indel mutations is an exercise inalignment, as the spurious indel rate on the sequencing platformsdisabled herein is relatively low (thus, even a handful of observationsof correctly aligned indels can be strong evidence of mutation).Accurate alignment in the presence of indels can be difficult however(especially as indel length increases). In addition to the generalissues associated with alignment, for example, of substitutions, theindel itself can cause problems with alignment. (For instance, adeletion of 2 bp of a dinucleotide repeat cannot be readily definitivelyplaced.) Both sensitivity and specificity can be reduced by incorrectplacement of shorter (<15 bp) apparent indel-containing reads. Largerindels (getting closer in magnitude to the length of individual reads—36bp in our current process) can cause failure to align the read at all,making detection of the indel impossible in the standard set of alignedreads.

Databases of cancer mutations can be used to address these problems andimprove performance. To reduce false positive indel discovery (improvespecificity), regions around commonly expected indels can be examinedfor problematic alignments due to sequence context and addressedsimilarly to substitutions above. To improve sensitivity of indeldetection, several different approaches of using information on theindels expected in cancer can be used. For example, short-readscontained expected indels can be simulated and alignment attempted. Thealignments can be studied and problematic indel regions can havealignment parameters adjusted, for instance by reducing gap open/extendpenalties or by aligning partial reads (for example, the first or secondhalf of a read).

Alternatively, initial alignment can be attempted not just with thenormal reference genome, but also with alternate versions of the genome,containing each of the known or likely cancer indel mutations. In thisapproach, reads of indels that initially failed to align or alignedincorrectly are placed successfully on the alternate (mutated) versionof the genome.

Additional exemplary alignment methodologies are known in the art, forexample, some of which are described in commonly owned, U.S. Ser. No.13/339,986 and PCT/US11/67725, both filed on Dec. 29, 2011, the contentsof which are incorporated by reference.

Mutation Calling

Base calling refers to the raw output of a sequencing device. Mutationcalling refers to the process of selecting a nucleotide value, forexample, A, G, T, or C, for a nucleotide position being sequenced.Typically, the sequencing reads (or base calling) for a position willprovide more than one value, for example, some reads will give a T andsome will give a G. Mutation calling is the process of assigning anucleotide value, for example, one of those values to the sequence.Although it is referred to as “mutation” calling it can be applied toassign a nucleotide value to any nucleotide position, for example,positions corresponding to mutant alleles, wildtype alleles, allelesthat have not been characterized as either mutant or wildtype, or topositions not characterized by variability. Methods for mutation callingcan include one or more of the following: making independent calls basedon the information at each position in the reference sequence (forexample, examining the sequence reads; examining the base calls andquality scores; calculating the probability of observed bases andquality scores given a potential genotype; and assigning genotypes (forexample, using Bayes rule)); removing false positives (for example,using depth thresholds to reject SNPs with read depth much lower orhigher than expected; local realignment to remove false positives due tosmall indels); and performing linkage disequilibrium (LD)/imputationbased analysis to refine the calls.

Equations to calculate the genotype likelihood associated with aspecific genotype and position are described, for example, in Li H. andDurbin R. Bioinformatics, 2010; 26(5): 589-95. The prior expectation fora particular mutation in certain cancer type can be used when evaluatingsamples from that cancer type. Such likelihood can be derived frompublic databases of cancer mutations, for example, Catalogue of SomaticMutation in Cancer (COSMIC), HGMD (Human Gene Mutation Database), TheSNP Consortium, Breast Cancer Mutation Data Base (BIC), and BreastCancer Gene Database (BCGD).

Examples of LD/imputation based analysis are described, for example, inBrowning B. L. and Yu Z. Am. J. Hum. Genet. 2009, 85(6):847-61. Examplesof low-coverage SNP calling methods are described, for example, in Li Y.et al., Annu. Rev. Genomics Hum. Genet. 2009, 10:387-406.

Mutation Calling: Substitutions

After alignment, detection of substitutions can be performed using acalling method, for example, Bayesian mutation calling method; which isapplied to each base in each of the subgenomic intervals, for example,exons of the gene to be evaluated, where presence of alternate allelesis observed. This method will compare the probability of observing theread data in the presence of a mutation with the probability ofobserving the read data in the presence of base-calling error alone.Mutations can be called if this comparison is sufficiently stronglysupportive of the presence of a mutation.

Methods have been developed that address limited deviations fromfrequencies of 50% or 100% for the analysis of cancer DNA. (for example,SNVMix-Bioinformatics. 2010 March 15; 26(6): 730-736.) Method disclosedherein however allow consideration of the possibility of the presence ofa mutant allele at anywhere between 1% and 100% of sample DNA, andespecially at levels lower than 50% This approach is particularlyimportant for the detection of mutations in low-purity FFPE samples ofnatural (multi-clonal) tumor DNA.

An advantage of a Bayesian mutation-detection approach is that thecomparison of the probability of the presence of a mutation with theprobability of base-calling error alone can be weighted by a priorexpectation of the presence of a mutation at the site. If some reads ofan alternate allele are observed at a frequently mutated site for thegiven cancer type, then presence of a mutation may be confidently calledeven if the amount of evidence of mutation does not meet the usualthresholds. This flexibility can then be used to increase detectionsensitivity for even rarer mutations/lower purity samples, or to makethe test more robust to decreases in read coverage. The likelihood of arandom base-pair in the genome being mutated in cancer is ˜1e-6. Thelikelihood of specific mutations at many sites in a typical multigeniccancer genome panel can be orders of magnitude higher. These likelihoodscan be derived from public databases of cancer mutations (for example,COSMIC).

Mutation Calling: Indels

Indel calling is a process of finding bases in the sequencing data thatdiffer from the reference sequence by insertion or deletion, typicallyincluding an associated confidence score or statistical evidence metric.

Methods of indel calling can include the steps of identifying candidateindel, calculating genotype likelihood through local re-alignment, andperforming LD-based genotype inference and calling. Typically, aBayesian approach is used to obtain potential indel candidates, and thenthese candidates are tested together with the reference sequence in aBayesian framework.

Algorithms to generate candidate indels are described, for example, inMcKenna A. et al., Genome Res. 2010; 20(9):1297-303; Ye K. et al.,Bioinformatics, 2009; 25(21):2865-71; Lunter G. and Goodson M. GenomeRes. 2010, epub ahead of print; Li H. et al., Bioinformatics 2009,Bioinformatics 25(16):2078-9.

Methods for generate indel calls and individual-level genotypelikelihoods include, for example, the Dindel algorithm (Albers C. A. etal., Genome Res. 2010 Oct. 27. [Epub ahead of print]). For example, theBayesian EM algorithm can be used to analyze the reads, make initialindel calls, and generate genotype likelihoods for each candidate indel,followed by imputation of genotypes using, for example, QCALL (Le S. Q.and Durbin R. Genome Res. 2010 Oct. 27. [Epub ahead of print]).Parameters, such as prior expectations of observing the indel can beadjusted (for example, increased or decreased), based on the size orlocation of the indels.

Additional exemplary mutation calling methodologies are known in theart, for example, some of which are described in commonly owned, U.S.Ser. No. 13/339,986 and PCT/US11/67725, both filed on Dec. 29, 2011, thecontents of which are incorporated by reference.

Examples

The present invention is additionally described by reference to thefollowing Examples, which are offered by way of illustration and are notintended to limit the invention in any manner. Standard techniques wellknown in the art or techniques specifically described below can beutilized.

Example 1. Hybridization of DNA Probe to the Capture Products

The procedure below summarizes the steps necessary for hybridization ofthe DNA probe with the capture products.

A. Hybridization

One hundred nanograms of pooled biotinylated baits, 500 ng of adaptedDNA library, 2 μg C_(o)t-1 DNA, 2 ng of oligonucleotide blockers 2.0 μLis combined into a volume of 10 μL and mixed with 10 μL of pre-warmedGenisphere Buffer 6 (2×SDS-Based Hybridization Buffer: 0.50M NaPO₄, 1%SDS, 2 mM EDTA, 2×SSC, 4×Denhardt's Solution). Following vortex mixingof the mixture, an overlay of 40 μL mineral oil is applied and themixture is denatured in a thermocycler at 95° C. for 5 minutes with aslow decrease to 71° C. The mixture is incubated at 71° C. for 48 hours.

B. Binding to Streptavidin Beads

The streptavidin beads are prepared in the following manner beforeaddition to the hybridization mixture. The streptavidin beads areallowed to sit at room temperature for 30 minutes. For eachhybridization reaction, 50 μL of Invitrogen M270 Streptavidin beads(magnetic) is washed twice with Bind and Wash Buffer (10 mM Tris-HCl (pH7.5), 2 M NaCl, 1 mM EDTA). The beads are resuspended in 80 μL thatincludes 50 μL Bind and Wash Buffer and 30 μL of water.

At the end of the 48 hour hybridization period, the 20 μL ofhybridization liquid is removed from under the mineral oil added to the80 μL of beads to provide a total volume of 100 μL. The mixture isrotated on tube rotator for 30 minutes to allow binding to occur betweenthe biotin on the hybridized template:bait complexes and thestreptavidin on the beads.

C. Washing the Streptavidin Beads

Following the rotation period, the samples are placed onto a magneticseparation rack. The beads are permitted to separate from thesupernatant, and the supernatant that contains DNA that did not bind tothe capture probes is removed and discarded. The probe bound beads iswashed sequentially with the following solutions. For each wash, thewash solution is added that has been pre-equilibrated to giventemperature, placed on rotator for the indicated time, is briefly spundown (magnet) and the supernatant is collected and discarded. The firstwash is with 1000 μL 1×SSC/0.1% SDS for 5 minutes, at 71° C. withrotation. The second wash is with 1000 0.1×SSC/0.1% SDS for 5 minutes,at 71° C. with rotation. The third wash is with 1000 μL 0.1×SSC/0.1% SDSfor 5 minutes, at 71° C. with rotation. The fourth wash is with 1000 μL0.1×SSC/0.1% SDS for 5 minutes, at RT, with rotation. The fifth wash iswith 1000 μL 0.2×SSC for 30 seconds, at RT, with tube still on magnet.The final wash solution is completely removed prior further processing,as explained below.

After the final wash, 50 μL 0.125 N NaOH is added and the mixture isincubated at RT for 10 minutes, with vortex treatment every 2 minutes tokeep beads in solution. The tube with the beads is placed back on themagnet for 1 minute. While beads are on magnet, an aliquot of 50 μL of 1M Tris-HCl (pH 8.8) is added to a new 1.5 mL RNAse/DNAse-free PCR tube.The supernatant from the tube on the magnet (0.125 N NaOH) is added tothe tube that contains the 1 M Tris-HCl (pH 8.8) to neutralize thesolution. The recovered template fragments are purified with AMPurebeads using 1.5× volume and eluting in 20 μL EB Buffer.

Example 2. PCR Reactions with Single-Stranded Template Material A. FinalPCR Enrichment

The recovered single-stranded templates (16 μL) are prepared to a totalvolume of 50 μL with the following reaction mix components (KAPA HiFimaster mix (25 μL); 25 μM Primer 1 (1 μL), 25 μM Primer 2 (1 μL), Water(7 μL)). The DNA is vortexed briefly and recollected as a solutionfollowing brief centrifugation. The reactions are placed into athermocycler with the following program: 98° C. (45 sec); 98° C. (15sec); 60° C. (30 sec); 72° C. (30 sec); 77° C. (30 sec) for five or morecycles. The amplified products are purified with AMPure beads using1.5×volume and eluting in 20 μL EB Buffer (Qiagen) (10 mM Tris-HCl, pH8.5). The resultant concentration of the DNA is measured with a QuibitFluorometer and diluted for use with the appropriate NGS sequencingplatform.

Five cycles of amplification are used for post-capture Ion Torrentlibraries and typically not more than 18 cycles of amplification areused for post-capture Illumina libraries. The standard Illumina protocolis optimized using the following PCR procedure. The recoveredsingle-stranded DNA templates (2 mL) is combined in a final volume of 50μL that includes 25 μL of SyberGreen MasterMix, 8 pmol of Primer 1, and8 pmol of Primer 2. The reactions are set up in 96-well qPCR plate tomimic the final PCR enrichment and run the following program: 95° C. (5min) followed by 30 cycles of 95° C. (30 sec) and 60° C. (45 sec). Thethreshold is manually adjusted to find the midpoint of the curve(halfway between where amplification starts and the plateau) and 3cycles from this value is subtracted to determine the number of cyclesto run for the final PCR enrichment. Three cycles are subtracted becausethe amount of DNA going into optimization is 8× less than what will beput into the final enrichment reaction; 2 μL of the neutralized capturedproduct goes into the PCR optimization reaction, and 16 μL will go intothe final PCR enrichment.

Example 3. T_(m)-Enhanced Oligonucleotides for Use in the IlluminaSequencing Platform with Inosine Bases for Barcode Domains

In Table I, the following blocking oligonucleotides were designed foruse in hybrid capture experiments for DNA template libraries with theIllumina sequencing platform. The T_(m)-enhanced oligonucleotides wereprepared using LNA (“+C” or “+A”) or BNA (“/iBNA-meC/” or “/iBNA-A/”) asT_(m)-enhancing groups. All oligonucleotides were prepared usingphosphoramidite chemical methods. T_(m) values are estimated for LNAbases in 750 mM NaCl buffer (similar ionic strength to 5×SSC) and for 15mM NaCl buffer (similar ionic strength to 0.1×SSC) using the method ofOwczarzy (Biochemistry 2011 50:9352-9367), which is incorporated byreference in its entirety. The BNA modification has similarthermodynamic effects as the LNA modification, so the predictionspresented herein apply to both classes of modified blockers and LNA/BNAmodifications can be substituted in all examples. For example,thermodynamic modeling in the examples below was done using LNA-derivednearest neighbor parameters while oligonucleotide synthesis was doneusing BNA bases.

TABLE I T_(m)-enhanced oligonucleotide blockers SEQ T_(m) (° C.)T_(m) (° C.) ID 750 mM 15 mM NO: Sequence #LNAs (Na) (Na) 1AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGAT 0 90.3 62.0 CTCGGTGGTCGCCGTATCATT2 AGATCGGAAGAGCGT+CGTGTAGGGAAAGAGTGTAGA 2 92.0 63.4TCT+CGGTGGTCGCCGTATCATT 3 AGAT+CGGAAGAGCGT+CGTGTAGGGAAAGAGTGTAG 4 93.965.0 ATCT+CGGTGGTCGC+CGTATCATT 4 AGAT+CGGAAGAGCGT+CGTGTAGGGAAAGAGTGTAG6 >95 66.6 ATCT+CGGTGGT+CGC+CGTAT+CATT 5AGAT+CGGAAGAG+CGT+CGTGTAGGGAAAGAGTGTA 8 >95 68.3GAT+CT+CGGTGGT+CGC+CGTAT+CATT 6 AGAT+CGGA+AGAG+CGT+CGTGT+AGGG+AAAGAGT12 >95 71.1 GTAGAT+CT+CGGTGGT+CG+C+CGTAT+CATT 7AG+AT+CGGA+AGAG+CGT+CGTGT+AGGG+A+A+AG 16 >95 73.3AGTGTAG+AT+CT+CGGTGGT+CG+C+CGTAT+CATT 8AG+AT+CGG+A+AG+AG+CGT+CGTGT+AGGG+A+A+AG+AGTGT+AG+AT+CT+CGGTGGT+CG+C+CGT+AT+ 22 >95 77.4 C+ATT

In the Table I, LNA-C T_(m) enhancing groups are included initially inthe T_(m)-enhanced oligonucleotides until all the C-positions (that is,9 positions having C) are exhaustively substituted, followed byinclusion of LNA-A T_(m) enhancing groups at the A-positions thereafter.

In Table II below, the design of a series of T_(m)-enhancedoligonucleotides for use as a blocker against the adaptor containing thebarcode sequence (8-inosines) is presented. As explained in the detaileddescription, there is no way to model the enhanced T_(m) valued withinosines (defined in sequences of Table II as “I” and “/ideoxyI/”)paired with variable bases. So, the inosine bases were not included inthe T_(m) analysis, but are present in the final sequence. The preciseenhanced T_(m) value for the actual sequences is readily determined byroutine empirical methods, however. The T_(m)-enhanced oligonucleotideswere prepared using LNA (“+C” or “+A”) or BNA (“/iBNA-meC/” or“/iBNA-A/”) as T_(m)-enhancing groups. All oligonucleotides wereprepared using phosphoramidite chemical methods.

TABLE II T_(m)-enhanced oligonucleotide blockers with barcode sequencesSEQ T_(m) (° C.) T_(m) (° C.) ID 750 mM 15 mM NO: Sequence #LNAs (Na)(Na) 9 GATCGGAAGAGCACACGTCTGAACTCCAGTCAC(III 0 89.8 61.7IIIII)ATCTCGTATGCCGTCTTCTGCTTG 10 GATCGGAAGAGCACACGTCTGAACTCCAGT+CAC(II2 91.5 63.1 IIIIII)ATCT+CGTATGCCGTCTTCTGCTTG 11GATCGGAAGAGCACACGTCTGAA+CTCCAGT+CAC 4 93.9 65.2(IIIIIIII)ATCT+CGTATGC+CGTCTTCTGCTTG 12GATCGGAAGAG+CACACGTCTGAA+CTCCAGT+CAC 6 >95 66.8(IIIIIIII)ATCT+CGTATGC+CGTCTTCTG+CTTG 13GAT+CGGAAGAG+CACACGTCTGAA+CTCCAGT+CA+C(IIIIIIII)ATCT+CGTATGC+CGTCTTCTG+CTT 8 >95 68.7 G 14GAT+CGGAAGAG+CACA+CGT+CTGAA+CTC+CAGT+CAC(IIIIIIII)ATCT+CGTATGC+CGT+CTT+CTG+ 12 >95 72.7 CTTG 15GAT+CGGAAGAG+CA+CA+CGT+CTGAA+CT+C+CAGT+CA+C(IIIIIIII)AT+CT+CGTATG+C+CGT+CT 17 >95 77.4 T+CTG+CTTG 16GAT+CGG+A+AGAG+CA+CA+CGT+CTG+AA+CT+C+CAGT+CA+C(IIIIIIII)+AT+CT+CGT+ATG+C+C 22 >95 80.4 GT+CTT+CTG+CTTG

In the Table II, LNA-C T_(m) enhancing groups are included initially inthe T_(m)-enhanced oligonucleotides until all the C-positions (that is,17 positions having C) are exhaustively substituted, followed byinclusion of LNA-A T_(m) enhancing groups at the A-positions thereafter.In this example, inosine bases were incorporated to span the barcodedomain.

Example 4. T_(m)-Enhanced Blocking Oligonucleotides for Use in IlluminaSequencing Platform with Mixed Bases (“N” Base) for Barcode Domains

In Table III, the following oligonucleotides were designed for use inhybrid capture experiments for DNA template libraries with the Illuminasequencing platform. The T_(m)-enhanced oligonucleotides were preparedusing LNA (“+C”, “+T” or “+A”) or BNA (“/iBNA-meC/”, “ABNA-T/”, or“/iBNA-A/”) as T_(m)-enhancing groups. All oligonucleotides wereprepared using phosphoramidite chemical methods.

TABLE IIIT_(m)-enhanced oligonucleotide blockers with barcode sequences (“N”) SEQT_(m) (° C.) T_(m) (° C.) ID 750 mM 15 mM NO: Sequence #LNAs (Na) (Na)17 IndexBlock: 0 ~90 61.8 CAAGCAGAAGACGGCATACGAGATNNNNNNGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT 18 IndexBlock+10-BNA: 10 >90 70.9CAAG+CAGAAGA+CGG+CATA+CGAGATNNNNNNGTGA+CTGGAGTT+CAGA+CGTGTG+CTCTT+C+CGATCT 19 IndexBlock+20-BNA: 20 >90 76.8CAAG+CAGAAGA+CGG+CA+TA+CGAGA+TNNNNNNG+TGA+C+TGGAG+T+T+CAGA+CG+TG+TG+CTC+TT+ C+CGA+TCT 20 IndexBlock_RevComp: 0~90 61.8 AGATCGGAAGAGCACACGTCTGAACTCCAGTCACNNNNNNATCTCGTATGCCGTCTTCTGCTTG 21 IndexBlock_RevComp+10-BNA: 10 >90 70.9AGAT+CGGAAGAG+CACA+CGTCTGAA+CTCCAGT+CA+CNNNNNNATCT+CGTATGC+CGT+CTTCTG+CTTG 22 IndexBlock_RevComp+20-BNA:20 >90 80.0 AGA+T+CGGAAGAG+CA+CA+CGT+CTGAA+CT+C+CAGT+CA+CNNNNNNAT+CT+CG+TA+TG+C+CGT+CT T+CTG+CTTG 23 PE1.0: 0 ~90 62.0AATGATACGGCGACCACCGAGATCTACACTCTTTCCC TACACGACGCTCTTCCGATCT 24PE1.0+10-BNA: 10 >90 72.6 AATGATA+CGG+CGA+CCA+CCGAGAT+CTACA+CTCTTTC+CCTACACGACGCT+CTTC+CGAT+CT 25 PE1.0+17-BNA: 17 >90 81.0AATGATA+CGG+CGA+CCA+CCGAGAT+CTA+CA+CT+CTTT+CC+CTA+CA+CGA+CG+CT+CTTC+CGAT+C T 26 PE1.0_Rev Comp: 0 ~90 62.0AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGAT CTCGGTGGTCGCCGTATCATT 27PE1.0_Rev Comp+9-BNA: 9 >90 69.0 AGAT+CGGAAGAG+CGT+CGTGTAGGGAAAGAGTGTAGAT+CT+CGGTGGT+CG+C+CGTAT+CATT 28 PE1.0_Rev Comp+20-BNA: 20 >90 77.3AG+AT+CGG+AAG+AG+CGT+CGTGT+AGGG+AA+AG+AGTGT+AG+AT+CT+CGGTGGT+CG+C+CGT+AT+C+ ATT

Table III provides examples where T_(m)-enhanced oligonucleotides weredesigned using either strand of the adaptor sequence as a blocker. Thepreferred strand for use as the T_(m)-enhanced oligonucleotide asblocker is one that provides maximal “blocking power” per modified group(that is, the largest optimal enhanced T_(m) value) with inclusion ofthe fewest T_(m)-enhancing groups. For example, compare SEQ ID NOS: 19and 22 (SEQ ID NO:22 being preferred) and SEQ ID NOS: 25 and 28 (SEQ IDNO:25 being preferred).

Example 5. T_(m)-Enhanced Oligonucleotides for Use in the Ion TorrentPGM Sequencing Platform

In Table IV, the following oligonucleotides were designed for use inhybrid capture experiments for DNA template libraries with the IonTorrent PGM sequencing platform. The T_(m)-enhanced oligonucleotideswere prepared using LNA (“+C” or “+A”) or BNA (“/iBNA-meC/” or“/iBNA-A/”) as T_(m)-enhancing groups. All oligonucleotides wereprepared using phosphoramidite chemical methods.

TABLE IVT_(m)-enhanced oligonucleotide blockers for Ion Torrent adaptors SEQT_(m) (° C.) T_(m) (° C.) ID 750 mM 15 mM NO: Sequence #LNAs (Na) (Na)29 Ion P1 top: 0 89.2 62.3 CCACTACGCCTCCGCTTTCCTCTCTATGGGCAGTCGG TGAT 30Ion P1 top 11C: 11 >90 77.9 C+CA+CTA+CGC+CTC+CG+CTTTC+CT+CT+CTATGGG+CAGT+CGGTGAT 31 Ion P1 bot: 0 89.6 62.1ATCACCGACTGCCCATAGAGAGGAAAGCGGAGGCGTA GTGGTT 32 Ion P1 bot 6C8A: 14 >9077.8 AT+CAC+CGA+CTGC+CC+AT+AG+AG+AGGA+A+AG+ CGG+AGG+CGT+AGTGGTT 33Ion A top: 0 83.2 57.4 CCATCTCATCCCTGCGTGTCTCCGACTCAG 34 Ion A top 11C:11 >90 76.1 C+CAT+CT+CAT+C+CCTG+CGTGT+CT+C+CGA+CT+ CAG 35 Ion A bot: 084.0 57.4 CTGAGTCGGAGACACGCAGGGATGAGATGGTT 36 Ion A bot 5C5A: 10 >9074.3 +CTG+AGT+CGG+AGA+CA+CG+CAGGG+ATG+AG+A TGGTT

Table IV provides additional examples were T_(m)-enhancedoligonucleotides may be designed using either strand of the adaptorsequence as a blocker. The preferred strand for use as theT_(m)-enhanced oligonucleotide as blocker is one that provides maximal“blocking power” per modified group (that is, the largest optimalenhanced T_(m) value) with inclusion of the fewest T_(m)-enhancinggroups. This example also shows that, depending upon the strand selectedas the T_(m)-enhanced oligonucleotide, LNA-C has superior “blockingpower” on a per T_(m)-enhancing group basis compared with LNA-A. Forexample, compare SEQ ID NOS: 30 and 32 (SEQ ID NO:30 being preferred)and SEQ ID NOS: 34 and 36 (SEQ ID NO:34 being preferred).

Examples A-O disclosed below present features of an embodiment for amethod for multigene analysis of a tumor sample, which is depictedthrough the flowchart provided in FIG. 3.

Example A: Nucleic Acid Isolation from a Tumor Sample

3×20 μm sections cut from a paraffin block were mixed with 400 μL BufferFTL by vortexing and incubated at 90° C. for 15 minutes in a 1.5 mLcentrifuge tube. A range of 88-92° C. was acceptable for the incubation.Then, the sample was incubated with 20 μL proteinase K at 55° C. for 6hours and 10 μL RNase (1 mg/mL) at room temperature for 5 minutes. Next,460 Buffer BL and 500 μL absolute ethanol were added to the sample. Theresulting sample solution was kept at room temperature until furtheruse.

To prepare the column for DNA binding, 100 μL Equilibration buffer wasadded to a MicroElute column and the column was centrifuged at 10,000×gfor 30 seconds. 700 μL of the sample solution described above wastransferred to the MicroElute column and the column was centrifuged at10,000×g for 1 minute. The centrifugation step was repeated if fluid didnot completely pass through MicroElute column. The remaining samplesolution was applied to the MicroElute column in the same way asdescribed above. Then, the MicroElute column was treated with 500 μLBuffer HB and centrifuged at 10,000×g for 1 minute. Next, 700 μL DNAWash Buffer diluted with ethanol was added into the MicroElute columnand the column was centrifuged at 10,000×g for 1 minute. The MicroElutecolumn was washed again using 700 μL DNA Wash Buffer diluted withethanol, centrifuged at 10,000×g for 1 minute, and centrifugedat >13,000×g for 3 minutes to dry the column. The MicroElute column wasplaced into a standard 1.5 mL centrifuge tube with the top removed.50-75 μL Elution Buffer preheated to 70° C. was added into the columnand incubated at room temperature for 3 minutes. The column wascentrifuged in collection tube at >13,000×g for 1 minute. Another 50-75μL Elution Buffer preheated to 70° C. was added into the MicroElutecolumn and incubated at room temperature for 3 minutes. The column wascentrifuged again in collection tube at >13,000×g for 1 minute. Theentire solution was transferred to a fresh 1.5 mL centrifuge tube andstored at −20° C.

FTL buffer, proteinase K, BL Buffer, Equilibration Buffer, MicroElutecolumn, Buffer HB, DNA Wash Buffer, and Elution Buffer were provided inE.Z.N.A.™ FFPE DNA Kit (OMEGA bio-tek, Norcross, Ga.; Cat. Nos.D3399-00, D3399-01, and D3399-02).

Additional methods to isolate nucleic acids (for example, DNA) fromformaldehyde- or paraformaldehyde-fixed, paraffin-embedded (FFPE)tissues are disclosed, for example, in Cronin M. et al., (2004) Am JPathol. 164(1):35-42; Masuda N. et al., (1999) Nucleic Acids Res.27(22):4436-4443; Specht K. et al., (2001) Am J Pathol. 158(2):419-429,Ambion RecoverAll™ Total Nucleic Acid Isolation Protocol (Ambion, Cat.No. AM1975, September 2008), Maxwell® 16 FFPE Plus LEV DNA PurificationKit Technical Manual (Promega Literature #TM349, February 2011), andQIAamp® DNA FFPE Tissue Handbook (Qiagen, Cat. No. 37625, October 2007).RecoverAll™ Total Nucleic Acid Isolation Kit uses xylene at elevatedtemperatures to solubilize paraffin-embedded samples and a glass-fiberfilter to capture nucleic acids. Maxwell® 16 FFPE Plus LEV DNAPurification Kit is used with the Maxwell® 16 Instrument forpurification of genomic DNA from 1 to 10 μm sections of FFPE tissue. DNAis purified using silica-clad paramagnetic particles (PMPs), and elutedin low elution volume. QIAamp® DNA FFPE Tissue Kit uses QIAamp® DNAMicro technology for purification of genomic and mitochondrial DNA.

Example B.1: Shearing of DNA

Covaris™ E210 instrument with circulating chiller was set to 4° C. Theinstrument water tank was filled with distilled/deionized water to level“6” on the fill-line. SonoLab™ software was launched and the system wasallowed to execute homing sequence when prompted. The water ininstrument tank was degassed for at least 45 minutes before shearingsamples.

To prepare the genomic DNA samples for shearing, samples were firstquantified using a PicoGreen® assay (Invitrogen) on a microplate reader(Spectramax M2, Molecular Devices) Based on the concentration, 120 μLdesired input DNA (2 ng/μl) with low TE (10 mM Tris, 0.2 mM EDTA, pH8.0) was used for the experiment. The 100 μl individual samples werepipetted slowly into the Covaris MicroTUBEs (Covaris Cat. #520045)through the septa in the lid of the tube. The Covaris MicroTUBEs werethen placed in the Covaris E-series tube rack. For 200 bp shearing, thesettings were as follows: 10% duty cycle, 5 Intensity, 200 cycles/burst,time 180 sec, and Frequency Sweeping mode. After shearing, the CovarisMicroTUBEs were briefly spun down using an appropriate adapter in amini-centrifuge, and the sheared samples were transferred to clean 1.5ml microcentrifuge tubes. Each sheared DNA sample was purified using aQIAGEN MinElute® column. Briefly, 5× QIAGEN PBI buffer was added to thesample in a 1.5 ml microcentrifuge tube (for example, 500 μl of PBIbuffer was added to 100 μl of sample). Each sample was vortexed, brieflyspun down, and transferred to a MinElute spin column. MinElute spincolumn was centrifuged at 13,000 rpm for 1 minute, and the flow-throughwas discarded. 750 μl of QIAGEN PE buffer was added to the column,centrifuged at 13,000 rpm for 1 minute, and the flow-through wasdiscarded. The spin column was centrifuged again at 13,000 rpm for 1minute and transferred to a clean 1.5 ml microcentrifuge tube. Thecolumn was air dried for 2-3 minutes. For the first elution, 18 μl ofQIAGEN Elution Buffer was added to each column, incubated for 2-3minutes, and then centrifuged at 13,000 rpm for 1 minute. For the secondelution, 15 μl of QIAGEN Elution Buffer was added, incubated for 1 min,and then centrifuged at 13,000 rpm for 1 minute. The eluent wascollected and the spin column was discarded.

Typically, 200 ng is used for DNA shearing, but the amount of DNA canrange from 20 to 200 ng or higher.

Example B.2: Alternative to DNA Shearing

This example describes an alternative method for DNA shearing fromExample 2A.

A double stranded genomic DNA is first denatured to single stranded DNA,and then mixed with primers, DNA polymerase (for example, Exo-DNApolymerase), dNTPs, and a small amount of ddNTPs. The primer sequencecan be a random hexamer, or a random hexamer tagged with an adaptorsequence at the 5′ end. Methods to use tagged random hexameramplification to clone and sequence minute quantities of DNA aredescribed, for example, in Wong K. K. et al., Nucleic Acids Res. 1996;24(19):3778-83. The reaction is incubated under the conditions thatallow primer-template annealing and DNA synthesis. The DNA synthesiswill terminate when a ddNTP is incorporated into the newly synthesizedfirst strand. The length of the synthesized first strand DNA can becontrolled by the ratio of dNTPs to ddNTPs. For example, the molar ratioof dNTPs to ddNTP is at least about 1000:1, about 5000:1, or about10000:1. After first strand synthesis, short fragments (such as primersand synthesized first strand DNA with short length and ddNTPs can beremoved by size selection (for example, using a size selection spincolumn). The resulting first strand DNA is mixed with primers (forexample, random hexamers or random hexamers tagged with an adaptorsequence), DNA polymerase (for example, Exo+ DNA polymerase), and dNTPs.An Exo+ DNA polymerase can be used to remove the terminal 3′-ddNTP fromthe first strand DNA or even to generate blunt ends over the secondpriming site. The reaction is then incubated under the conditions thatallow primer-template annealing and DNA synthesis. After synthesis ofthe second strand, the resulting double stranded DNA fragments can bepurified and used directly in library construction. Alternatively, thedouble stranded DNA fragments can be PCR amplified using primerscontaining adaptor sequences if these adaptor sequences have beenincluded in the primers for first- and second-strand synthesis. Theprimers for PCR amplification can also include the entire sequencesand/or bar code sequences.

Example C: Library Preparation End Repair Reaction

End-repair reagents (NEB #E6050L) were thawed and an end-repairmastermix was prepared on ice. To prepare 70 μl of mastermix per sample,55 μl nuclease free water was mixed with 10 μl 10× End Repair reactionbuffer and 5 μl End Repair enzyme mix. Then 70 μl of mastermix was addedto 30 μl of each sheared DNA sample in a 96 well PCR plate on ice. Thereaction was incubated in a thermocycler at 20° C. for 30 minutes. Eachsample was purified using a QIAGEN MinElute® column. Briefly, 5× QIAGENPBI buffer was added to sample (for example, 500 μl of PBI buffer wasadded to 100 μl of sample) in a 1.5 ml microcentrifuge tube. Each samplewas vortexed, briefly spun down, and transferred to a MinElute spincolumn. MinElute spin column was centrifuged at 13,000 rpm for 1 minute,and the flow-through was discarded. 750 μl of QIAGEN PE buffer was addedto the column, centrifuged at 13,000 rpm for 1 minute, and theflow-through was discarded. The spin column was centrifuged again at13,000 rpm for 1 minute and transferred to a clean 1.5 mlmicrocentrifuge tube. The column was air dried for 2-3 minutes. For thefirst elution, 22 μl of QIAGEN Elution Buffer (10 mM Tris, pH8.5) wasadded to each column, incubated for 2-3 min, and then centrifuged at13,000 rpm for 1 minute. For the second elution, 22 μl of QIAGEN ElutionBuffer was added, incubated for 1 min, and then centrifuged at 13,000rpm for 1 minute. The eluent was collected and the spin column wasdiscarded.

3′ A-Base Addition

A-base addition reagents (NEB #E6053L) were thawed on ice and an A-baseaddition mastermix was prepared on ice. To prepare 10 μl of mastermixper sample, 2 μl nuclease-free water was mixed with 5 μl 10× dA-Tailingreaction buffer and 3 μl Klenow Fragment (3′->5′ exo-). 10 μl ofmastermix was added to 40 μl of each purified end-repaired DNA sample ina 96 well PCR plate on ice. The reaction was incubated in a thermocyclerat 37° C. for 30 min. Each sample was purified using a QIAGEN MinElute®column. Briefly, 5× QIAGEN PBI buffer was added to sample (for example,250 μl of PBI buffer was added to 50 μl of sample) in a 1.5 mlmicrocentrifuge tube. Each sample was vortexed, briefly spun down, andtransferred to a MinElute spin column. MinElute spin column wascentrifuged at 13,000 rpm for 1 minute, and the flow-through wasdiscarded. 750 μl of QIAGEN PE buffer was added to the column,centrifuged at 13,000 rpm for 1 minute, and the flow-through wasdiscarded. The spin column was centrifuged again at 13,000 rpm for 1minute and transferred to a clean 1.5 ml microcentrifuge tube. Thecolumn was air dried for 2-3 min. For the first elution, 13 μl of QIAGENElution Buffer (10 mM Tris, pH8.5) was added to each column, incubatedfor 2-3 min, and then centrifuged at 13,000 rpm for 1 minute. For thesecond elution, 13 μl of QIAGEN Elution Buffer was added, incubated for1 min, and then centrifuged at 13,000 rpm for 1 minute. The eluent wascollected and the spin column was discarded.

Ligation of Multiplex Adaptors

Ligation reagents (NEB #E6056L) were thawed and a ligation mastermix wasprepared on ice. To prepare 36 μl of mastermix per sample, 12 μl 5×Quick Ligation reaction buffer was added to 3.3 μl Illumina MultiplexAdaptor (15 uM, included in Illumina Cat. #PE-400-1001) (3.3 μladaptor/1 μg starting input DNA was used). For example, for one sampleof 500 ng input DNA, the adaptors were first diluted in water (2 μladaptors plus 2 μl H2O), then 3.3 μl of this diluted adaptor mix, 15.7μl of nuclease free water, and 5 μl of Quick T4 DNA ligase were added tothe ligation reaction. For >1 μg starting material, >3.3 μl of adaptorswere used. Thus, less water was added to keep the total volume ofdiluted adaptor mix and nuclease free water at 19 μl.

36 μl of mastermix and 24 μl of each dA-tailed DNA sample were added tothe wells of a 96 well PCR plate on ice. The reaction was incubated in athermocycler at 25° C. for 30 min. Each sample was purified using aQIAGEN MinElute® column. Briefly, 5× QIAGEN PBI buffer was added tosample (for example, 300 μl of PBI buffer was added to 60 μl of sample)in a 1.5 ml microcentrifuge tube. Each sample was vortexed, briefly spundown, and transferred to a MinElute spin column. MinElute spin columnwas centrifuged at 13,000 rpm for 1 minute, and the flow-through wasdiscarded. 750 μl of QIAGEN PE buffer was added to the column,centrifuged at 13,000 rpm for 1 minute, and the flow-through wasdiscarded. The spin column was centrifuged again at 13,000 rpm for 1minute and transferred to a clean 1.5 ml microcentrifuge tube. Thecolumn was air dried for 2-3 minutes. For the first elution, 20 μl ofQIAGEN Elution Buffer (10 mM Tris, pH8.5) was added to each column,incubated for 2-3 minutes, and then centrifuged at 13,000 rpm for 1minute. For the second elution, 20 μl of QIAGEN Elution Buffer wasadded, incubated for 1 minute, and then centrifuged at 13,000 rpm for 1minute. The eluent was collected and the spin column was discarded.

PCR Enrichment

PCR reagents were thawed and a PCR mastermix was prepared on ice. For 62μl of mastermix per sample, 50 μl of 2× Phusion High Fidelity mastermixwith HF Buffer (Finnzyme, NEB Cat. # F-531 S), 8 μl nuclease-free water,2 μl Illumina Primer 1.0 (25 μM), and 2 μl Illumina Primer 2.0 (0.5 μM)were used. Then 62 μl of mastermix was mixed with 2 μl Illumina IndexPrimer (25 μM included in Illumina Cat. # PE-400-1001) with appropriatebar code and 36 μl of ligated DNA sample in a 96-well PCR plate.

The reaction was incubated in a thermocycler as follows:

 1 Cycle 98° C. 30 sec 18 Cycles 98° C. 10 sec 65° C. 30 sec 72° C. 30sec  1 Cycle 72° C.  5 min  4° C. hold

Each PCR reaction was size selected with 1.8× volume of AMPureXP beads(Agencourt; Beckman Coulter Genomics Cat. # A6388). Briefly, 1.8×AMPureXP beads were added to sample (for example, 180 μl of beads wereadded to 100 μl of sample) in a 1.5 ml microcentrifuge tube, vortexed,and incubated for 5 minutes with end-over-end rotation mixing. Tubeswere placed on a magnet stand until the solution cleared (2 minutes).The supernatant was discarded without disturbing the beads captured onthe magnet. 600 μl of freshly-made 70% ethanol was added to the beards,incubated for 1 min followed by removal of the ethanol. A second aliquotof 600 μl freshly-made 70% ethanol was added to the beads, incubated for1 minute, and the ethanol was removed. The tubes were put back on themagnet stand for 1-2 minutes to re-capture the beads. Any remainingethanol was removed and the beads were air dried at room temperature for5-10 minutes. 30 μl of QIAGEN Elution Buffer was added to the beads,vortexed, and incubated for 2 minutes. Tubes were placed back on themagnet stand until the solution cleared (2 minutes). The supernatant wastransferred to a fresh 1.5 mL tube and the beads were discarded. Theeluted DNA samples were quantified using a Q-PCR assay. Thesequantifications will allow for equimolar pooling to ensure equalrepresentation of each library within a pooled hybrid capture selection.

Example D: Hybrid Selection Pool Indexed Sample Libraries

Pools (up to 12-plex) of libraries that had been indexed, purified, andquantified by Q-PCR were made on ice. Equimolar pools were prepared in1.5 ml microcentrifuge tubes to ensure that each sample was representedin the hybrid selection process equally. The total input of DNA for eachof these pools can range from 2000 ng to 500 ng. Typically, the totalinput DNA is 2000 ng. Thus, if twelve samples are pooled, 166.67 ng ofeach can be pooled to achieve a total of 2000 ng. The final volume of a2000 ng library pool should be 4 μl. Due to varying concentrations ofthe indexed libraries a pool can be made with any larger volume but thenthe pool should be dried down by speedvac (using low heat) andreconstituted in 4 μl of nuclease-free water.

The greater the yield in a library construction, the greater thecomplexity of the library.

Hybridization of the Pooled DNA Libraries to Biotinylated-RNA Baits

Agilent SureSelect Target Enrichment Paired End kit (#G3360A-J) was usedin this experiment. Hybridization Buffer #3, SureSelect Block #1,SureSelect Block #2, Paired End Primer 1.0 block, Index Primer 1-12block, RNAse block, and biotinylated-RNA bait were thawed on ice.

The following mastermixes were prepared:

a. Hybridization Buffer Mix (13 μl per reaction):

-   -   i. Hybridization Buffer #1 (Agilent)—25 μl    -   ii. Hybridization Buffer #2 (Agilent)—1 μl    -   iii. Hybridization Buffer #3 (Agilent)—10 μl    -   iv. Hybridization Buffer #4 (Agilent)—13 μl        b. Blocking Mix (8 μl per reaction):    -   i. SureSelect Block #1 (Agilent)—2.5 μl    -   ii. SureSelect Block #2 (Agilent)—2.5 μl    -   iii. Paired End primer 1.0 block (IDT, resuspended to 200 μM        with H₂O)—1.5 μl    -   iv. Index Primer 1-12 block (IDT, resuspended to 200 μM with        H₂O)—1.5 μl        c. Dilution of RNase Block    -   i. For custom biotinylated RNA-baits with territory <3 Mb: 1 μl        of RNase Block (Agilent) was diluted in 9 μl of water.    -   ii. For custom baits with a bait territory >3 Mb: 1 μl of RNase        block was diluted in 3 μl of water (still 0.5 μl of RNase block        per 7 μL capture reaction)        d. Bait Mix: (7 μl per reaction)    -   i. RNA Baits—2 μl (for baits which have a bait territory >3 Mb,        5 μl bait was used)    -   ii. Diluted RNase Block—5 μl (for baits which have a bait        territory >3 Mb, 2 μl RNase block diluted as indicated above was        used)

Once the Hybridization Buffer Mix, Blocking Mix, and Bait Mix(es) wereprepared, the hybridization buffer mix was vortexed, spun down, andheated to 65° C. in the heat block. 4 μl of each pooled sample libraryto be hybrid selected was mixed with 8 μl of the blocking mix in a 96well PCR plate. The reaction was incubated in a thermocycler at 95° C.for 5 minutes and then held at 65° C. When the pooled samplelibraries/blocking mix had been incubating at 95° C. for 5 min and thenat 65° C. for 2.5 minutes, the bait mix (=bait/RNAse block mix) were putin the heat block at 65° C. for 2.5 minutes. The hybridization buffercontaining tubes were quickly spun down, and then immediately returnedto 65° C. heat block. 13 μl of the heated hybridization buffer mix waspipetted into each sample library/block mix while the 96 well plateremained in the thermocycler at 65° C. Once the bait mix had beenincubated for 2.5 minutes at 65° C., 7 μl of the bait mix was added toeach sample library/block/hybridization buffer mix while the 96 wellplate remained in the thermocycler at 65° C. The reaction (total volumewas 32 μl) was incubated at 65° C. for 24 hours in a thermocycler.

Preparation of the Magnetic Beads

SureSelect Wash Buffer #2 was prewarmed at 65° C. in the heat block.Dynal MyOne Streptavidin T1 beads (Invitrogen) were vortexed andresuspended. The beads were washed by adding 200 μl of SureSelectBinding Buffer per 50 μl Dynal beads (for example, 1200 μl of SureSelectBinding Buffer was used to prepare 300 μl of Dynal beads). The beadswere vortexed for 5 seconds and spun down briefly. The beads were placedon a magnet stand for about 15 seconds or until all the beads werecaptured. The supernatant was removed and discarded. Wash was repeatedwith SureSelect Binding Buffer two more times for a total of threewashes. After washing, the beads were resuspended in 200 μl ofSureSelect Binding Buffer per 50 μl Dynal beads (for example, 1200 μl ofSureSelect Binding Buffer was used to prepare 300 μl of Dynal beads).The resuspended beads were vortexed and spun down briefly. 200 μl ofresuspended beads were aliquoted into individual 1.5 ml microcentrifugetubes.

Selection of the Hybrid Captured DNA

After 24 hours of incubation, each hybridized sample from the PCR platein the thermocycler at 65° C. was quickly pipetted into a tubecontaining 200 μl of prepared beads at room temperature. The mixtures ofsample and beads were vortexed for 5 seconds and incubated on a rotatorat room temperature for 30 minutes, to ensure proper mixing. Then thetubes were quickly spun down. The beads were captured on a magnet (for 2minutes) and the supernatant was removed and discarded. The beads wereresuspended in 500 μl of SureSelect Wash Buffer #1, for a low stringencywash. The samples were vortexed for 5 seconds and incubated for 15 minat room temperature off the magnet. Samples were vortexed for 5 secondsevery 3-5 minutes. The tubes were quickly spun down. The beads were thencaptured on a magnet stand for 2 minutes and the supernatant was removedand discarded. For a high stringency wash to remove off-target material,the beads were washed with SureSelect Wash Buffer #2 preheated to 65° C.Briefly, the beads were resuspended in 500 μl of prewarmed SureSelectWash Buffer #2 and mixed on a vortexer for 5 seconds to resuspend thebeads. The beads were briefly spun down in a centrifuge and incubated at65° C. for 10 min in a heat block with occasional vortex mixing for 5seconds at room temperature. Then the beads were briefly spun down in acentrifuge and captured on a magnet for 2 minutes. Wash was repeated 2more times with prewarmed SureSelect Wash Buffer #2 at 65° C. for atotal of three washes. Then the wash buffer was completely removed and50 μl of SureSelect Elution Buffer was added to the beads following byvortexing for 5 seconds to mix the beads. The samples were incubated for10 minutes at room temperature with occasional vortex mixing for 5seconds. The beads were briefly spun down in a centrifuge and capturedon a magnet stand. The supernatant containing the captured DNA waspipetted to a new 1.5 ml microcentrifuge tube. 50 μl of SureSelectNeutralization Buffer was added to the captured DNA. Samples were vortexfor 5 seconds, briefly spun down in a centrifuge, and purified using1.8× volume of AMPureXP beads. DNA was eluted in 40 μl nuclease-freewater.

PCR Enrichment of the Captured DNA

PCR reagents were thawed and a PCR mastermix was prepared on ice. For 60μl of mastermix per sample, 50 μl 2× Phusion High Fidelity mastermixwith HF buffer (NEB #F-531S) was mixed with 8 μl nuclease-free water, 1μl QPCR Primer1.1 (100 μM in H2O), and 1 μl QPCR Primer2.1 (100 μM inH2O). The primer sequences for Q-PCR are:

QPCR Primer1.1 (HPLC-purified from IDT): (SEQ ID NO: 79)5′AATGATACGGCGACCACCGAGAT3′ QPCR Primer2.1 (HPLC-purified from IDT):(SEQ ID NO: 80) 5′CAAGCAGAAGACGGCATACGA3′

60 μl of mastermix was added to 40 μl of each purified captured DNAsample in a 96 well PCR plate. The reaction was incubated in athermocycler as follows:

 1 Cycle 98° C. 30 sec 12 Cycles 98° C. 10 sec 65° C. 30 sec 72° C. 30sec  1 Cycle 72° C.  5 min  4° C. Hold

Each 100 μl of PCR reaction was purified with 1.8× volume of AMPureXPbeads and eluted in 35 μl of elution buffer (10 mM Tris, pH 8.5). Thehybrid selected/captured DNA samples were quantified using a Q-PCRassay. The Q-PCR assay detected the end adaptors and the reads indicatedhow much of each sample should be loaded on a sequencing flow cell toget the appropriate cluster density.

Example E: Methods

The following exemplifies certain embodiments of the methods andexperimental conditions used to identify the alterations according tothe Examples. Additional translocation screening can be done using, forexample, either qRT-PCR analysis of cDNA prepared from a pre-selectedtumor sample.

Massively parallel DNA sequencing was done on hybridization captured,adaptor ligation-based libraries using DNA isolated from archived fixedparaffin-embedded tissue. A combination of analysis tools were used toanalyze the data and assign DNA alteration calls. Additionaltranslocation screening was done using either qRT-PCR analysis of cDNAprepared from frozen tumors or IHC assessment of archived FFPEspecimens. Massively parallel cDNA sequencing was performed to confirmexpression of both novel translocations using RNA isolated from FFPEtissue. Matched normal reference genomic DNA from blood was sequencedfor the index NSCLC patient to confirm the somatic origin of therearrangement.

Genomic DNA Sequencing

Sequencing of 2574 exons of 145 cancer genes was done using DNA fromarchived formalin fixed paraffin embedded (FFPE) tumor specimens; 24from NSCLC patients. Sequencing libraries were constructed by theadaptor ligation method using genomic DNA followed by hybridizationselection with optimized RNA hybridization capture probes (AgilentSureSelect custom kit). Sequencing on the HiSeq2000 instrument(Illumina) was done using 36×36 paired reads to an average depth of253×. Data processing and mutation assignments for base substitutions,indels, copy number alterations and genomic rearrangements were doneusing a combination of tools optimized for mutation calling from tumortissue.

cDNA Sequencing

cDNA was generated from total RNA extracted from a single 5-10 um FFPEtissue section using the Roche High Pure kit and reverse transcribed tocDNA with random hexamer primers by the SuperScript® III First-StrandSynthesis System (Invitrogen). Double stranded cDNA was made with theNEBNext® mRNA Second Strand Synthesis Module (New England Biolabs) andused as input to library construction, hybrid capture and sequencing asfor FFPE DNA samples. Analysis of expression levels was done with acombination of analysis tools.

Example F: Exemplary Selected Genes and Variants for Multiplex Analysis

This example provides four exemplary tables summarizing a selection ofgenes, variants and cancer types for multiplex analysis.

TABLE 1 List of exemplary selected genes and variants, associated cancertypes, and priority codons for multiplex analysis. Gene Hugo GeneCategory Cancer Types Priority Codons ABL1 Priority 1 Leukemia (forexample, chronic 315 myeloid leukemia (CML), acute myeloid leukemia(AML), acute lymphoblastic leukemia (ALL)) AKT1 Priority 1 breastcancer, colorectal cancer, ovarian cancer ALK Priority 1 Lymphoma (forexample, non- Hodgkin lymphoma, anaplastic large- cell lymphoma (ALCL)),inflammatory myofibroblastic tumor APC Priority 1 Colorectal cancer,medulloblastoma, 1114, 1338, 1450, 1556 mismatch repair cancer syndromeAR Priority 1 Prostate cancer BRAF Priority 1 Lung cancer, non-Hodgkin600 lymphoma, colorectal cancer, thyroid cancer, melanoma CDKN2APriority 1 melanoma, pancreatic cancer, Li- Fraumeni syndrome, lungcancer (for example, non-small cell lung cancer (NSCLC)), squamous cellcarcinoma, retinoblastoma, astrocytoma CEBPA Priority 1 Leukemia (forexample, acute myeloid leukemia (AML), acute myeloid leukemia (AML),monoblastic leukemia), retinoblastoma CTNNB1 Priority 1 Colorectalcancer, ovarian cancer, 32, 33, 34, 37, 41, 45 prostate cancer, livercancer (for example, hepatoblastoma (HB), hepatocellular carcinoma(HCC)), pilomatrixoma, medulloblastoma, salivary gland pleiomorphicadenomas EGFR Priority 1 Lung cancer, squamous cell 719, 746-750, 768,790, 858, carcinoma, glioblastoma, glioma, 861 colorectal cancer ERBB2Priority 1 Gastric cancer, glioma, ovarian cancer, lung cancer ESR1Priority 1 Breast cancer, endometrial cancer, endometrialadenocarcinoma, leiomyoma, mammary ductal carcinoma FGFR1 Priority 1Leukemia, lymphoma FGFR2 Priority 1 Breast cancer, prostate cancer FGFR3Priority 1 Bladder cancer, cervical cancer, multiple myeloma, FLT3Priority 1 Leukemia (for example, acute 835 myeloid leukemia (AML),acute promyelocytic leukemia, acute lymphoblastic leukemia) HRASPriority 1 Hurthle cell thyroid carcinoma, 12, 13, 61 bladder cancer,melanoma, colorectal cancer JAK2 Priority 1 Leukemia (for example,chronic 617 lymphoblastic leukemia (CLL), acute lymphoblastic leukemia(ALL), chronic myelogenous leukemia (CML), acute myelogenous leukemia(AML)) KIT Priority 1 Gastrointestinal stromal tumor 816 (GIST),testicular tumor, leukemia (for example, acute myeloid leukemia (AML)),mast cell tumor, mesenchymal tumor, adenoid cystic carcinoma, lungcancer (for example, small cell lung cancer), lymphoma (for example,Burkitt lymphoma) KRAS Priority 1 Leukemia (for example, acute 12, 13,61 myelogenous leukemia (AML), juvenile myelomonocytic leukemia (JMML)),colorectal cancer, lung cancer MET Priority 1 Gastric cancer,hepatocellular carcinoma (HCC), hereditary papillary renal carcinoma(HPRC), lung cancer (for example, non-small cell lung cancer), papillarythyroid carcinoma, glioma, esophageal adenocarcinoma, osteosarcoma,endometrial cancer, squamous cell carcinoma, melanoma, breast cancer MLLPriority 1 Leukemia (for example, acute lymphoblastic leukemia (ALL),acute myeloid leukemia (AML) MYC Priority 1 chronic lymphocytic leukemia(CLL), Burkitt lymphoma, plasmacytoma, NF1 Priority 1 Leukemia (forexample, juvenile myelomonocytic leukemia (JMML)), neurofibroma, NOTCH1Priority 1 Squamous cell carcinoma, leukemia 1575, 1601 (for example,acute lymphoblastic leukemia (ALL)), medullary thyroid carcinoma,lymphoma (for example, thymic lymphoma, T-cell lymphoma) NPM1 Priority 1Lymphoma (for example, non- Hodgkin lymphoma, anaplastic large celllymphoma, anaplastic lymphoma), leukemia (for example, acutepromyelocytic leukemia, acute myelogenous leukemia (AML)) NRAS Priority1 Leukemia (for example, juvenile 12, 13, 61 myelomonocytic leukemia(JMML), acute myeloid leukemia (AML), acute lymphoblastic leukemia),melanoma, PDGFRA Priority 1 Gastrointestinal stromal tumor (GIST),leukemia (for example, chronic eosinophilic leukemia (CEL), acutelymphocytic leukemia (ALL)), mesenchymal tumor PIK3CA Priority 1Colorectal cancer, breast cancer, 88, 542, 545, 546, 1047, ovariancancer, hepatocellular 1049 carcinoma, head and neck squamous cellcarcinoma (HNSCC), anaplastic thyroid carcinoma, endometrial cancer,gallbladder adenocarcinoma, glioblastoma PTEN Priority 1 Head and necksquamous cell 130, 173, 233, 267 carcinomas (HNSCC), endometrial cancer,glioma, prostate cancer, glioblastoma RB1 Priority 1 Retinoblastoma,bladder cancer, osteosarcoma, lung cancer (for example, small cell lungcancer, non- small cell lung cancer), leukemia (for example, acutelymphoblastic leukemia (ALL)) RET Priority 1 Colorectal cancer,medullary thyroid 918 carcinoma, multiple neoplasia type 2B,pheochromocytoma, multiple neoplasia type 2A, thyroid papillarycarcinoma, thryoid cancer, retinoblastoma TP53 Priority 1 TP53 isfrequently mutated or 175, 245, 248, 273, 306 inactivated in about 60%of cancers, for example, esophageal squamous cell carcinoma, Li-Fraumenisyndrome, head and neck squamous cell carcinomas (HNSCC), lung cancer,hereditary adrenocortical carcinoma, astrocytoma, squamous cellcarcinoma, bladder cancer, colorectal cancer, glioblastoma,retinoblastoma ABL2 Cancer Gene Acute myeloid leukemia (AML) AKT2 CancerGene Ovarian cancer, pancreatic cancer AKT3 Cancer Gene Melanoma,glioma, uternine cancer, prostate cancer, oral cancer, ovarian cancerARAF Cancer Gene Angioimmunoblastic T-cell lymphoma, ehrlich ascitestumor ARFRP1 Cancer Gene Breast cancer ARID1A Cancer Gene Neuroblastoma,acute lymphoblastic leukemia (ALL), neuroendocrine tumor ATM Cancer GeneLeukemia (for example, T-cell prolymphocytic leukemia (T-PLL)),lymphoma, medulloblastoma, glioma ATR Cancer Gene Pyothorax-associatedlymphoma, T- cell lymphoma AURKA Cancer Gene Laryngeal squamous cellcarcinoma, ovarian cancer, bladder cancer, head and neck squamous cellcarcinoma (HNSCC), laryngeal carcinoma, esophageal squamous cellcarcinoma (ESCC), pancreatic cancer AURKB Cancer Gene Colorectal cancer,astrocytoma, ependymal tumor, glioma, esophageal squamous cell carcinoma(ESCC), acute myeloid leukemia (AML) BCL2 Cancer Gene Lymphoma,colorectal adenocarcinoma, esophageal squamous cell carcinoma (ESCC),synovial sarcoma, leukemia BCL2A1 Cancer Gene Pulmonary granuloma,gastric adenoma, burkitt lymphoma, parotid adenoma, kaposi sarcoma,gastric cancer, colon cancer BCL2L1 Cancer Gene Head and neck squamouscell carcinoma, glioblastoma, mesothelioma, pancreatic cancer,adenocarcinoma lung BCL2L2 Cancer Gene Brain cancer, leukemia, lymphoma,colorectal adenocarcinoma, colorectal cancer, adenoma, cervical squamouscell carcinoma BCL6 Cancer Gene Lymphoma, leukemia BRCA1 Cancer GeneBreast cancer, ovarian cancer BRCA2 Cancer Gene Breast cancer, ovariancancer, pancreatic cancer CARD11 Cancer Gene Lymphoma CBL Cancer GeneLymphoma, leukemia CCND1 Cancer Gene Chronic lymphoblastic leukemia(CLL), B-cell acute lymphoblastic leukemia (B-ALL), breast cancer CCND2Cancer Gene Retinoblastoma, mantle cell lymphoma, T-cell acutelymphoblastic leukemia (T-ALL), Burkitt lymphoma, testicular germ celltumor, ovarian granulosa cell tumor, multiple myeloma CCND3 Cancer GeneRetinoblastoma, mantle cell lymphoma, anaplastic large cell lymphoma,lymphoma (non- hodgkins), B-cell lymphoma, laryngeal squamous cellcarcinoma, indolent lymphoma, null cell adenoma CCNE1 Cancer Gene Breastcancer, ovarian cancer, bladder cancer, retinoblastoma CDH1 Cancer GeneGastric cancer, lobular carcinoma, squamous cell carcinoma, invasiveductal carcinoma, invasive lobular carcinoma CDH2 Cancer Gene Melanoma,malignant mesothelioma, pleural mesothelioma, desmoplastic melanoma,lung adenocarcinoma, endometrioid tumor, mesothelioma, bladder cancer,esophageal squamous cell carcinoma (ESCC) CDH20 Cancer Gene Breastcancer CDH5 Cancer Gene Granuloma, epithelioid sarcoma CDK4 Cancer GeneMelanoma Category CDK6 Cancer Gene Acute lymphoblastic leukemia (ALL)CDK8 Cancer Gene Colon cancer, lung cancer, rectal cancer, acutelymphoblastic leukemia (ALL) CDKN2B Cancer Gene Leukemia,retinoblastoma, laryngeal squamous cell carcinoma CDKN2C Cancer GeneThyroid carcinoma, pituitary adenoma, oligodendroglioma, pancreaticendocrine tumor, multiple myeloma, hepatoblastoma, lymphoid tumor,multiple endocrine neoplasia type 1, anaplastic oligodendroglioma CHEK1Cancer Gene Leukemia, colon cancer CHEK2 Cancer Gene Breast cancer CRKLCancer Gene Leukemia, lymphoma CRLF2 Cancer Gene Leukemia DNMT3A CancerGene Testicular germ cell tumor, lymphosarcoma, hepatocellularcarcinoma, salivary gland tumor DOT1L Cancer Gene Leukemia EPHA3 CancerGene Rhabdomyosarcoma, lymphoma, prostate cancer, hepatocellularcarcinoma, leukemia, melanoma EPHA5 Cancer Gene Glioblastoma, breastcancer, astrocytoma, Wilms' tumor, glioma EPHA6 Cancer Gene Breastcancer EPHA7 Cancer Gene Glioblastoma multiforme (GBM), colon cancer,duodenal cancer, parathyroid tumor, prostate cancer EPHB1 Cancer GeneColorectal cancer, embryonal carcinoma, gastric cancer, teratocarcinoma,mucinous carcinoma EPHB4 Cancer Gene Head and neck squamous cellcarcinoma (HNSCC), brain cancer, endometrial cancer, ovarian cancerEPHB6 Cancer Gene Neuroblastoma, melanoma, non- small cell lung cancer(NSCLL) ERBB3 Cancer Gene Breast cancer, non-small cell lung cancer(NSCLC), pancreatic cancer, invasive ductal carcinoma, lungadenocarcinoma, endometrioid carcinoma, pilocytic astrocytoma ERBB4Cancer Gene Breast cancer, medulloblastoma, cervical squamous cellcarcinoma, prostate cancer, leukemia ERG Cancer Gene Prostate cancer,Ewing's sarcoma, leukemia, prostate cancer ETV1 Cancer Gene Prostatecancer, breast cancer, Ewing's sarcoma, desmoplastic small round celltumor, myxoid liposarcoma, clear cell sarcoma ETV4 Cancer Gene Breastcancer, ovarian cancer, squamous cell carcinoma tongue, Ewing's sarcomaETV5 Cancer Gene Ganglioglioma, brain tumor ETV6 Cancer Gene Leukemia,congenital fibrosarcoma, secretory carcinoma, myelodysplastic syndromeEWSR1 Cancer Gene Ewing's sarcoma, clear cell sarcoma, desmoplasticsmall round cell tumor, extraskeletal myxoid chondrosarcoma, myxoidliposarcoma, angiomatoid fibrous histiocytoma EZH2 Cancer Gene Prostatecancer, gallbladder adenocarcinoma, breast cancer, bladder cancer,gastric cancer, Ewing's sarcoma FANCA Cancer Gene Leukemia FBXW7 CancerGene Colorectal cancer, endometrial cancer, T-cell acute lymphoblasticleukemia (T-ALL) FGFR4 Cancer Gene Pituitary tumor, prostate cancer,lung cancer, astrocytoma, rhabdomyosarcoma, pituitary adenoma,fibroadenoma FLT1 Cancer Gene Breast cancer, prostate cancer FLT4 CancerGene Lung cancer, Kaposi's sarcoma, gastric cancer, lymphangioma,squamous cell carcinoma FOXP4 Cancer Gene Lymphoma, brain tumor GATA1Cancer Gene Megakaryoblastic leukemia of Downs Syndrome GNA11 CancerGene Breast cancer GNAQ Cancer Gene Uveal melanoma GNAS Cancer GenePituitary adenoma GPR124 Cancer Gene Colon cancer GUCY1A2 Cancer GeneBreast cancer HOXA3 Cancer Gene Breast cancer HSP90AA1 Cancer GeneLymphoma, myeloma IDH1 Cancer Gene Glioblastoma multiforme (GBM) IDH2Cancer Gene Glioblastoma multiforme (GBM) IGF1R Cancer Gene Ewing'ssarcoma, breast cancer, uveal melanoma, adrenocortical carcinoma,pancreatic cancer IGF2R Cancer Gene Gastrointestinal tumor, liver cancerIKBKE Cancer Gene Breast cancer IKZF1 Cancer Gene Lymphoma, leukemiaINHBA Cancer Gene Erythroleukemia, barrett metaplasia, esophagealadenocarcinoma, granulosa cell tumor, sex cord- stromal tumor, lungadenocarcinoma, pheochromocytoma, krukenberg tumor, ovarian cancer IRS2Cancer Gene Hyperinsulinemia, uterine leiomyosarcoma JAK1 Cancer GeneLeukemia, ovarian cancer, breast cancer JAK3 Cancer Gene Acutelymphoblastic leukemia (ALL) JUN Cancer Gene Skin cancer, leukemia KDRCancer Gene Non-small cell lung cancer (NSCLC), angiosarcoma LRP1BCancer Gene Lung cancer, gastric cancer, esophageal cancer LTK CancerGene Lymphoma, breast cancer MAP2K1 Cancer Gene Prostate cancer, gastriccancer MAP2K2 Cancer Gene Pancreatic cancer, intestinal tumor MAP2K4Cancer Gene Pancreatic cancer, breast cancer, colorectal cancer MCL1Cancer Gene Multiple myeloma, leukemia, lymphoma MDM2 Cancer GeneSarcoma, glioma, colorectal cancer MDM4 Cancer Gene Glioblastomamultiforme (GBM), bladder cancer, retinoblastoma MEN1 Cancer GeneParathyroid tumor MITF Cancer Gene Melanoma MLH1 Cancer Gene Colorectalcancer, endometrial cancer, ovarian cancer, CNS cancer MPL Cancer GeneMyeloproliferative disorder (MPD) MRE11A Cancer Gene Breast cancer,lymphoma MSH2 Cancer Gene Colorectal cancer, endometrial cancer, ovariancancer MSH6 Cancer Gene Colorectal cancer MTOR Cancer Gene Lymphoma lungcancer, renal cancer, clear cell carcinoma, glioma MUTYH Cancer GeneColorectal cancer MYCL1 Cancer Gene Small cell lung cancer (SCLC) MYCNCancer Gene Neuroblastoma NF2 Cancer Gene Meningioma, acoustic neuroma,renal cancer NKX2-1 Cancer Gene Lung cancer, thyroid cancer,adenocarcinoma NTRK1 Cancer Gene Papillary thyroid cancer NTRK3 CancerGene Congenital fibrosarcoma, secretory breast cancer PAK3 Cancer GeneLung cancer PAX5 Cancer Gene Non-Hodgkin Lymphoma (NHL), acutelymphoblastic leukemia (ALL, for example, B-cell ALL) PDGFRB Cancer GeneMyeloproliferative disorder (MPD), acute myeloid leukemia (AML), chronicmyeloid leukemia (CML), chronic myelomonocytic leukemia (CMML) PIK3R1Cancer Gene Glioblastoma, ovarian cancer, colorectal cancer PKHD1 CancerGene Pancreatic cancer PLCG1 Cancer Gene Head and neck cancer, leukemiaPRKDC Cancer Gene Glioma, glioblastoma, gastric cancer, ovarian cancerPTCH1 Cancer Gene Skin basal cell, medulloblastoma PTPN11 Cancer GeneJuvenile myelomonocytic leukemia (JMML), acute myeloid leukemia (AML),myelodysplastic syndromes (MDS) PTPRD Cancer Gene Lung cancer, cutaneoussquamous cell carcinoma, glioblastoma, neuroblastoma RAF1 Cancer GenePilocytic astrocytoma RARA Cancer Gene Leukemia RICTOR Cancer Gene Coloncancer, lymphoma, glioma, breast cancer RPTOR Cancer Gene Breast cancer,prostate cancer RUNX1 Cancer Gene Acute myeloid leukemia (AML), pre-B-cell acute lymphoblastic leukemia (preB-ALL), T-cell acutelymphoblastic leukemia (T-ALL) SMAD2 Cancer Gene esophageal squamouscell carcinoma (ESCC) SMAD3 Cancer Gene Skin cancer, choriocarcinomaSMAD4 Cancer Gene Pancreatic cancer, colon cancer SMARCA4 Cancer GeneNon-small cell lung cancer (NSCLC) SMARCB1 Cancer Gene Malignantrhabdoid SMO Cancer Gene Skin basal cell cancer SOX10 Cancer GeneOligodendroglioma SOX2 Cancer Gene Embryonal carcinoma, germ cell tumorSRC Cancer Gene Sarcoma, colon cancer, breast cancer STK11 Cancer GeneNon-small cell lung cancer (NSCLC), pancreatic cancer TBX22 Cancer GeneBreast cancer TET2 Cancer Gene Myelodysplastic syndromes (MDS) TGFBR2Cancer Gene Lung cancer, gastric cancer, colon cancer TMPRSS2 CancerGene Prostate cancer TOP1 Cancer Gene Acute myeloid leukemia (AML) TSC1Cancer Gene Hamartoma, renal cell cancer TSC2 Cancer Gene Hamartoma,renal cell cancer USP9X Cancer Gene Leukemia VHL Cancer Gene Renalcancer, hemangioma, pheochromocytoma WT1 Cancer Gene Wilms' tumor,desmoplastic small round cell tumor ABCB1 PGx Gene ABCC2 PGx Gene ABCC4PGx Gene ABCG2 PGx Gene C1orf144 PGx Gene CYP1B1 PGx Gene CYP2C19 PGxGene CYP2C8 PGx Gene CYP2D6 PGx Gene CYP3A4 PGx Gene CYP3A5 PGx GeneDPYD PGx Gene ERCC2 PGx Gene ESR2 PGx Gene FCGR3A PGx Gene GSTP1 PGxGene ITPA PGx Gene LRP2 PGx Gene MAN1B1 PGx Gene MTHFR PGx Gene NQO1 PGxGene NRP2 PGx Gene SLC19A1 PGx Gene SLC22A2 PGx Gene SLCO1B3 PGx GeneSOD2 PGx Gene SULT1A1 PGx Gene TPMT PGx Gene TYMS PGx Gene UGT1A1 PGxGene UMPS PGx Gene

“Priority 1” refers to the highest priority of selected genes or geneproducts.

“Cancer Genes” refer to cancer-associated genes or gene products of lesspriority relative to Priority 1.

“PGx Genes” refers to genes that are important for pharmacogenetics andpharmacogenomics (PGx).

TABLE 1A Additional exemplary selected genes and variants, associatedcancer types, priority codons, actionability category, and potentialtherapies. Hugo Gene Priority Actionability Gene Category Cancer TypesCodons Category Reason ASXL1 Priority 1 Multiple myeloma (MM) DPrognostic (neg MDS) BACH1 Priority 1 Breast C PARP Inhibitors BAP1Priority 1 Uveal melanoma, breast, NSCLC C PARP Inhibitors BARD1Priority 1 Breast C PARP Inhibitors BLM Priority 1 Leukemia, lymphoma,skin C squamous cell, other cancers BRIP1 Priority 1 Acute myeloidleukemia (AML), C PARP Inhibitors leukemia, breast CDKN1B Priority 1Breast D CREBBP Priority 1 Acute lymphoblastic leukemia (ALL), D AML,DLBCL, B-cell non-Hodgkin's lymphoma (B-NHL) DDR2 Priority 1 NSCLC CDasatinib EMSY Priority 1 Breast C PARP Inhibitors FANCC Priority 1 AML,leukemia C PARP inhibitor FANCD2 Priority 1 AML, leukemia C PARPinhibitor FANCE Priority 1 AML, leukemia C PARP inhibitor FANCF Priority1 AML, leukemia C PARP inhibitor FANCG Priority 1 AML, leukemia C PARPinhibitor FANCL Priority 1 AML, leukemia C PARP inhibitor HGF Priority 1MM C Resistance NFKB1 Priority 1 Breast D Possible POOR PROGNOSIS NOTCH2Priority 1 Marginal zone lymphoma, DLBCL D — PALB2 Priority 1 Wilmstumor, medulloblastoma, C PARP Inhibitors AML, breast PBRM1 Priority 1Clear cell renal carcinoma, breast E HDAC inhibitors? PDK1 Priority 1NSCLC C PDK1 inhibitors PIK3R2 Priority 1 NSCLC C PI3K-PATHWAYINHIBITORS RAD50 Priority 1 Breast C PARP Inhibitors RAD51 Priority 1Breast C PARP Inhibitors ROS1 Priority 1 Glioblastoma, NSCLC C SF3B1Priority 1 MDS, CML, ALL, pancreatic, breast E SPOP Priority 1 Malignantmelanoma E ACVR1B Cancer Gene Pancreas, breast E ALOX12B Cancer GeneMultiple myeloma (MM) E ATRX Cancer Gene Pancreatic neuroendocrinetumors E AXL Cancer Gene Non small cell lung cancer (NSCLC), E MM BCORCancer Gene Breast E BCORL1 Cancer Gene Breast E C17orf39 Cancer GeneBreast E CASP8 Cancer Gene Breast E CBFB Cancer Gene AML E CD22 CancerGene NSCLC, breast E CD79A Cancer Gene Diffuse large B-cell lymphoma E(DLBCL) CD79B Cancer Gene DLBCL E CDC73 Cancer Gene Parathyroid E CDK12Cancer Gene Ovarian E CHUK Cancer Gene Colorectal E CRBN Cancer GeneUpper aerodigestive tract E CSF1R Cancer Gene NSCLC E CTCF Cancer GeneBreast E CTNNA1 Cancer Gene Breast E CUL4A Cancer Gene Leukemia E CUL4BCancer Gene Leukemia E CYP17A1 Cancer Gene Breast E DAXX Cancer GenePancreatic neuroendocrine tumors E DIS3 Cancer Gene MM E EP300 CancerGene Colorectal, breast, pancreatic, AML, E ALL, DLBCL ERCC2 Cancer GeneSkin basal cell, skin squamous cell, E melanoma FAM46C Cancer Gene MM EFGF1 Cancer Gene Breast E FGF10 Cancer Gene Breast E FGF12 Cancer GeneBreast E FGF14 Cancer Gene Breast E FGF19 Cancer Gene Breast E FGF23Cancer Gene Breast E FGF3 Cancer Gene Breast E FGF4 Cancer Gene Breast EFGF6 Cancer Gene Breast E FGF7 Cancer Gene Breast E FOXL2 Cancer GeneGranulosa-cell tumour of the ovary 134 E GATA2 Cancer Gene AML, ChronicMyeloid Leukemia E (CML, blast transformation) GATA3 Cancer Gene BreastE GRAF Cancer Gene AML, myelodysplastic syndrome E (MDS) GRIN2A CancerGene Malignant melanoma E GSK3B Cancer Gene NSCLC E HLA-A Cancer Gene MME IGF1 Cancer Gene Breast E IGF2 Cancer Gene Breast E IL7R Cancer GeneT-cell acute lymphoblastic leukemia E (T-ALL) INSR Cancer Gene NSCLC,glioblastoma, gastric E IRF4 Cancer Gene Multiple myeloma (MM) E KDM4CCancer Gene Ovarian, breast E KDM5A Cancer Gene AML E KDM6A Cancer GeneRenal, oesophageal squamous cell E carcinoma (SCC), MM KEAP1 Cancer GeneNSCLC E KLHL6 Cancer Gene Chronic lymphocytic leukaemia (CLL) E LMO1Cancer Gene T-cell acute lymphoblastic leukemia E (T-ALL), neuroblastomaLRP6 Cancer Gene NSCLC, malignant melanoma E LRRK2 Cancer Gene Ovarian,NSCLC E MAGED1 Cancer Gene MM E MAP3K1 Cancer Gene Breast E MAP3K13Cancer Gene Breast E MLL2 Cancer Gene Medulloblastoma, renal E MLST8Cancer Gene Breast E MYD88 Cancer Gene Activated B cell-like-DLBCL (ABC-E DLBCL) MYST3 Cancer Gene Breast E NCOR1 Cancer Gene Breast E NFE2L2Cancer Gene NSCLC, head and neck squamous cell E carcinoma (HNSCC)NFKBIA Cancer Gene Breast E NOTCH3 Cancer Gene NSCLC, breast E NOTCH4Cancer Gene NSCLC, breast E NSD1 Cancer Gene AML E NTRK2 Cancer GeneRenal, NSCLC E NUP93 Cancer Gene Breast E PAK7 Cancer Gene NSCLC,malignant melanoma E PHLPP2 Cancer Gene Ovarian, glioblastoma, NSCLC EPHOX2B Cancer Gene Neuroblastoma E PIK3C2G Cancer Gene NSCLC E PIK3C3Cancer Gene NSCLC E PIK3CG Cancer Gene NSCLC E PNRC1 Cancer Gene MM EPRDM1 Cancer Gene DLBCL E PRKAR1A Cancer Gene Adrenal gland, thyroid EPRSS8 Cancer Gene Breast E PTCH2 Cancer Gene Malignant melanoma E PTK2Cancer Gene NSCLC, glioblastoma E PTK2B Cancer Gene NSCLC, breast E RELCancer Gene Hodgkin Lymphoma E RHEB Cancer Gene NSCLC, colorectal EROCK1 Cancer Gene Breast E RUNXT1 Cancer Gene NSCLC, colorectal E SETD2Cancer Gene Clear cell renal carcinoma E SH2B3 Cancer GeneMyelodysplastic syndrome (MDS) E SOCS1 Cancer Gene DLBCL E SPEN CancerGene Adenoid cystic carcinoma E STAG2 Cancer Gene Glioblastoma E STAT3Cancer Gene Breast E STAT4 Cancer Gene Breast E STK12 Cancer Gene PNET,NSCLC E SUFU Cancer Gene Medulloblastoma E TBX23 Cancer Gene Breast ETBX3 Cancer Gene Breast E TNFAIP3 Cancer Gene Marginal zone B-celllymphomas, E Hodgkin's lymphoma, primary mediastinal B cell lymphomaTNFRSF14 Cancer Gene Follicular lymphoma E TNFRSF17 Cancer GeneIntestinal T-cell lymphoma E TNKS Cancer Gene NSCLC E TNKS2 Cancer GeneMelanoma, breast E TRRAP Cancer Gene Colorectal, glioblastoma E TYK2Cancer Gene NSCLC, breast E XBP1 Cancer Gene MM E XPO1 Cancer GeneChronic lymphocytic leukaemia (CLL) E ZNF217 Cancer Gene Breast E ZNF703Cancer Gene Breast E

The actionability categories are classified as described below. Table 1Bprovides a summary of the application of the different categories toexemplary alterations in different cancer types.

Category A: Approved/standard alterations that predict sensitivity orresistance to approved/standard therapies

KRAS G13D in metastatic colon cancer

ERBB2 amplification in breast cancer

EGFR L858R in non small cell lung cancer

Category B: Alterations that are inclusion or exclusion criteria forspecific experimental therapies

KRAS G13D in colon cancer, lung cancer, or breast cancer

BRAF V600E in melanoma, colon cancer, or lung cancer

NRAS Q61K in melanoma

PIK3CA H1047R in breast cancer

FGFR1 amplification in breast cancer

PTEN biallelic inactivation in breast cancer

BRCA1 biallelic inactivation in breast cancer or pancreatic cancer

Category C: Alterations with limited evidence (early clinical data,conflicting clinical data, pre-clinical data, theoretical) that predictsensitivity or resistance to standard or experimental therapies

KRAS Q61H in colon cancer (early clinical)

PIK3CA H1047R in breast cancer (conflicting clinical)

BRAF V600E in colon cancer (conflicting clinical)

ERBB2 mutation or amplification in lung cancer (case reports)

BRAF D594G in lung cancer (pre-clinical)

FGFR1 amplification in breast cancer (pre-clinical)

ATM biallelic inactivation in breast cancer (pre-clinical)

TSC1 biallelic inactivation in colon cancer (pre-clinical)

ATR biallelic inactivation in breast cancer (theoretical)

BRAF V600E mutation in sarcoma (theoretical)

Category D: Alterations with prognostic or diagnostic utility in aparticular subtype of cancer

MSH2 biallelic inactivation in colon cancer (strong clinical evidence)

BRAF V600E in colon cancer (strong clinical evidence)

KRAS G13D in lung cancer (strong clinical evidence)

BRCA1 inactivation in breast cancer (strong clinical evidence)

Category E: Alterations with clear biological significance in cancer(that is, driver mutations) without clear clinical implications

APC biallelic inactivation in colon cancer

TP53 biallelic inactivation in breast cancer

MITF amplification in melanoma

ARID1A in ovarian cancer

Category F: Alterations without Known Biological Significance in CancerNovel Alterations in Known Cancer Genes

Targets of Therapy

Orthologues of Known Cancer Genes

TABLE 1B Exemplary Classification of Alterations in Different CancerTypes A B C D E KRAS G13D Colon Cancer x x x x KRAS G13D Lung Cancer x xx KRAS G13D Breast Cancer x x NRAS Q61K Melanoma x x x KRAS Q61H ColonCancer x x x BRAF V600E Melanoma x x BRAF V600E Colon Cancer x x x xBRAF V600E Lung Cancer x x BRAF D594G Lung Cancer x x PIK3CA H1047RBreast Cancer x x x PIK3CA H1047R Colon Cancer x x x EGFR L858R LungCancer x x EGFR T790M Lung Cancer x x x ERBB2 Amplification BreastCancer x x BRCA1 biallelic inactivation Breast Cancer x x x x BRCA2biallelic inactivation Pancreatic Cancer x x x x ATM biallelicinactivation Breast Cancer x x TSC biallelec inactivation Colon Cancer xx PTEN biallelic inactivation Colon Cancer x x PTEN biallelicinactivation Breast Cancer x x x VHL biallelic inactivation KidneyCancer x x MSH2 biallelic inactivation Colon Cancer x x ATR bialleicinactiation Breast Cancer x x MYC amplification Breast Cancer x x

TABLE 2 Exemplary selected genes associated with pharmacogenetics andpharmacogenomics (PGx). Gene Locus Mutation Effect ABCB1 chr7: 869765813853C > T Better survival in Asian AML treated with Ida/AraC; Survivalin breast cancer patients treated with paclitaxel ABCB1 chr7: 869985542677G > T/A Response to taxanes, platinums and GI toxicity; Bettersurvival in Asian AML treated with Ida/AraC ABCC2 chr10: 101610761Doxcetaxel induced leukopenia ABCC4 chr13: 94613416 6MP Toxicity ABCG2chr4: 89252551 MTX ABCG2 chr4: 89271347 q141K Diarrhea after gefitinibABCG2 chr4: 89274403 MTX C1orf144 chr1: 16578662 Toxicity fromdaunorubicin CYP1B1 chr2: 38151707 CYP1B1*3 Toxicity from daunorubicin;Survival in breast cancer patients treated with paclitaxel CYP2C19chr10: 96509051 CYP2C19*17 Improved benefit from tamoxifen CYP2C19chr10: 96511647 CYP2C19*17 Improved benefit from tamoxifen CYP2C8 chr10:96786964 461delV Paclitexel metabolism CYP2C8 chr10: 96788739 K399RPaclitexel metabolism CYP2C8 chr10: 96808096 Paclitexel metabolismCYP2C8 chr10: 96808109 Paclitexel metabolism CYP2C8 chr10: 96817020Paclitexel metabolism CYP2D6 chr22: 40853554 CYP2D6: 3183 CYP2D6*29,present in Tanzanians G > A CYP2D6 chr22: 40853749 CYP2D6: 2988CYP2D6*41 (IM) G > A CYP2D6 chr22: 40853887 CYP2D6: 2850 CYP2D6*2 (EM)C > T CYP2D6 chr22: 40854122 CYP2D6: 2613-2615 CYP2D6*9 (unclearfunction?) del AGA CYP2D6 chr22: 40854188 CYP2D6: 2549 CYP2D6*3 del ACYP2D6 chr22: 40854891 CYP2D6: 1846 CYP2D6*4 G > A CYP2D6 chr22:40855030 CYP2D6: 1707 CYP2D6*6 del T CYP2D6 chr22: 40855078 CYP2D6:CYP2D6*29, present in Tanzanians 1659G > A CYP2D6 chr22: 40855716CYP2D6: 1023 Present in CYP2D6*17 C > T CYP2D6 chr22: 40856638 CYP2D6:Present in CYP2D6*10 (casuative) and *4 100C > T (associated) CYP3A4chr7: 99196395 CYP3A4 chr7: 99196460 CYP3A4 chr7: 99197606 CYP3A4 chr7:99204017 CYP3A4 chr7: 99204029 CYP3A4*16B Paclitaxel metabolism inJapanese CYP3A4 chr7: 99205328 CYP3A4 chr7: 99205363 CYP3A4 chr7:99219597 CYP3A4 chr7: 99220032 CYP3A4*1B Greater clearance of docetaxelCYP3A5 chr7: 99088330 CYP3A5 chr7: 99100771 CYP3A5 chr7: 99108475 DPYDchr1: 97688202 DPYD*2A Toxicity to 5FU DPYD chr1: 97753983 DPYD*5Toxicity to 5FU DPYD chr1: 97937679 496A > G 5FU, Xeloda toxicity DPYDchr1: 98121473 DPYD*9A Toxicity to 5FU ERCC2 chr19: 50546759 2251A > CRelapse after 5FU in Asians ESR1 chr6: 152205074 Tamoxifen inducedhypercholesterolemia ESR2 chr14: 63769569 Tamoxifen inducedhypercholesterolemia FCGR3A chr1: 159781166 V158F Response to cetuximabFGFR4 chr5: 176452849 GLY388ARG GSTP1 chr11: 67109265 I105V Resistanceto multiple chemotherapies GSTP1 chr11: 67110155 A114V Unclear, linkagedisequlibrium with I105V ITPA chr20: 3141842 6MP Toxicity LRP2 chr2:169719231 Associated with ototoxicity from cisplatin MAN1B1 chr9:139102689 Toxicity from daunorubicin MTHFR chr1: 11777044 MTX MTHFRchr1: 11777063 MTX MTHFR chr1: 11778965 677C > T MTX NQO1 chr16:68302646 NQO1*2 Rapid degradation (cisplatin, doxorubicin); poorsurvival in breast cancer treated with anthracyclines NRP2 chr2:206360545 Toxicity from daunorubicin SLC19A1 chr21: 45782222 MTX SLC22A2chr6: 160590272 Ala270Ser Reduced cisplatin nephrotoxicity SLCO1B3chr12: 20936961 Doxcetaxel induced leukopenia SOD2 chr6: 160033862 V16AInferior survival in breast cancer treated with cyclophosphamide SULT1A1chr16: 28524986 SULT1A1 chr16: 28525015 SULT1A1 chr16: 28528073 SULT1A1chr16: 28528301 TMPT chr6: 18247207 TPMT*3B Purine toxicity TPMT chr6:18238897 6 MP Toxicity TPMT chr6: 18238991 6 MP Toxicity TPMT chr6:18251934 6 MP Toxicity TYMS chr18: 647646 28 bp tandem Toxicity to 5FUrepeat TYMS chr18: 663451 6 bp deletion Toxicity to 5FU UGT1A1 chr2:234255266 Anemia from irinotecan UGT1A1 chr2: 234255709 thrombocytopeniafrom irinotecan UGT1A1 chr2: 234330398 UGT1A1*60 UGT1A1 chr2: 234330521UGT1A1*93 UGT1A1 chr2: 234333620 UGT1A1*28 UGT1A1 chr2: 234333883UGT1A1*6 UGT1A1 chr2: 234334358 UGT1A1*27 UMPS chr3: 125939432 Gly213AlaToxicity to 5FU

TABLE 3 Exemplary selected genes associated with translocation mutationsin solid tumors Gene Hugo Gene Category Translocation Partner CancerTypes ACSL3 Priority 1 ETV1 prostate ALK Priority 1 NPM1, TPM3, TFG,TPM4, ATIC, ALCL, NSCLC, Neuroblastoma CLTC, MSN, ALO17, CARS, EML4 BRAFPriority 1 AKAP9, KIAA1549 melanoma, colorectal, papillary thyroid,borderline ov, Non small-cell lung cancer (NSCLC), cholangiocarcinoma,pilocytic astrocytoma C15orf21 Priority 1 ETV1 prostate CANT1 Priority 1ETV4 prostate CCND1 Priority 1 IGH, FSTL3 CLL, B-ALL, breast DDX5Priority 1 ETV4 prostate ELK4 Priority 1 SLC45A3 prostate EML4 Priority1 ALK NSCLC EP300 Priority 1 MLL, RUNXBP2 colorectal, breast,pancreatic, AML ERG Priority 1 EWSR1, TMPRSS2, ELF4, FUS, Ewing sarcoma,prostate, AML HERPUD1 ETV1 Priority 1 EWSR1, TMPRSS2, SLC45A3, Ewingsarcoma, prostate C15orf21, HNRNPA2B1. ACSL3 ETV4 Priority 1 EWSR1,TMPRSS2, DDX5, KLK2, Ewing sarcoma, Prostate carcinoma CANT1 ETV5Priority 1 TMPRSS2, SCL45A3 Prostate FGFR3 Priority 1 IGH@, ETV6bladder, MM, T-cell lymphoma HERPUD1 Priority 1 ERG prostate HNRNPA2B1Priority 1 ETV1 prostate KLK2 Priority 1 ETV4 prostate RET Priority 1H4, PRKAR1A, NCOA4, PCM1, medullary thyroid, papillary thyroid, GOLGA5,TRIM33, KTN1, TRIM27, pheochromocytoma HOOK3 ROS1 Priority 1 GOPC, ROS1glioblastoma, NSCLC SLC45A3 Priority 1 ETV1, ETV5, ELK4, ERG prostateTMPRSS2 Priority 1 ERG, ETV1, ETV4, ETV5 prostate AKAP9 BRAF papillarythyroid ASPSCR1 TFE3 alveolar soft part sarcoma ATF1 EWSR1, FUSmalignant melanoma of soft parts, angiomatoid fibrous histiocytoma BRD3NUT lethal midline carcinoma of young people BRD4 NUT lethal midlinecarcinoma of young people C12orf9 LPP lipoma CD74 ROS1 NSCLC CDH11 USP6aneurysmal bone cysts CHCHD7 PLAG1 salivary adenoma CHN1 TAF15extraskeletal myxoid chondrosarcoma CIC DUX4 soft tissue sarcoma CMKOR1HMGA2 lipoma COL1A1 PDGFB, USP6 dermatofibrosarcoma protuberans,aneurysmal bone cyst COX6C HMGA2 uterine leiomyoma CREB1 EWSR1 clearcell sarcoma, angiomatoid fibrous histiocytoma CREB3L2 FUS fibromyxoidsarcoma CRTC3 MAML2 salivary gland mucoepidermoid CTNNB1 PLAG1colorectal, cvarian, hepatoblastoma, others, pleomorphic salivaryadenoma D10S170 RET, PDGFRB papillary thyroid, CML DDIT3 FUS liposarcomaDUX4 CIC soft tissue sarcoma ELKS RET papillary thyroid ETV6 NTRK3,RUNX1, PDGFRB, ABL1, congenital fibrosarcoma, multiple MN1, ABL2, FACL6,CHIC2, leukemia and lymphoma, secretory ARNT, JAK2, EVI1, CDX2, STL,breast, MDS, ALL HLXB9, MDS2, PER1, SYK, TTL, FGFR3, PAX5 EWSR1 FLI1,ERG, ZNF278, NR4A3, FEV, Ewing sarcoma, desmoplastic small ATF1, ETV1,ETV4, WT1, ZNF384, round cell tumor, ALL, clear cell CREB1, POU5F1, PBX1sarcoma, sarcoma, myoepithelioma FEV EWSR1, FUS Ewing sarcoma FLI1 EWSR1Ewing sarcoma FOXO1A PAX3 alveolar rhabdomyosarcomas FUS DDIT3, ERG,FEV, ATF1, liposarcoma, AML, Ewing sarcoma, CREB3L2 angiomatoid fibroushistiocytoma, fibromyxoid sarcoma GOLGA5 RET papillary thyroid HEI10HMGA2 uterine leiomyoma HMGA1 ? microfollicular thyroid adenoma, variousbenign mesenchymal tumors HMGA2 LHFP, RAD51L1, LPP, HEI10, lipoma COX6C,CMKOR1, NFIB HOOK3 RET papillary thyroid JAZF1 SUZ12 endometrial stromaltumours KTN1 RET papillary thyroid LHFP HMGA2 lipoma LIFR PLAG1 salivaryadenoma LPP HMGA2, MLL, C12orf9 lipoma, leukemia MAML2 MECT1, CRTC3salivary gland mucoepidermoid MECT1 MAML2 salivary gland mucoepidermoidMN1 ETV6 AML, meningioma MYB NFIB adenoid cystic carcinoma MYC IGK,BCL5, BCL7A, BTG1, TRA, Burkitt lymphoma, amplified in other IGHcancers, B-CLL NCOA1 PAX3 alveolar rhadomyosarcoma NCOA4 RET papillarythyroid NFIB MYB, HGMA2 adenoid cystic carcinoma, lipoma NONO TFE3papillary renal cancer NR4A3 EWSR1 extraskeletal myxoid chondrosarcomaNTRK1 TPM3, TPR, TFG papillary thyroid NTRK3 ETV6 congenitalfibrosarcoma, Secretory breast NUT BRD4, BRD3 lethal midline carcinomaof young people OMD USP6 aneurysmal bone cysts PAX3 FOXO1A, NCOA1alveolar rhabdomyosarcoma PAX7 FOXO1A alveolar rhabdomyosarcoma PAX8PPARG follicular thyroid PBX1 TCF3, EWSR1 pre B-ALL, myoepithelioma PCM1RET, JAK2 papillary thyroid, CML, MPD PDGFB COL1A1 DFSP PDGFRA FIP1L1GIST, idiopathic hypereosinophilic syndrome PLAG1 TCEA1, LIFR, CTNNB1,CHCHD7 salivary adenoma POU5F1 EWSR1 sarcoma PPARG PAX8 follicularthyroid PRCC TFE3 papillary renal PRKAR1A RET papillary thyroid PRO1073TFEB renal cell carcinoma (childhood epithelioid) RAD51L1 HMGA2 lipoma,uterine leiomyoma RAF1 SRGAP3 pilocytic astrocytoma SFPQ TFE3 papillaryrenal cell SRGAP3 RAF1 pilocytic astrocytoma SS18 SSX1, SSX2 synovialsarcoma SS18L1 SSX1 synovial sarcoma SSX1 SS18 synovial sarcoma SSX2SS18 synovial sarcoma SSX4 SS18 synovial sarcoma SUZ12 JAZF1 endometrialstromal tumours TAF15 TEC, CHN1, ZNF384 extraskeletal myxoidchondrosarcomas, ALL TCEA1 PLAG1 salivary adenoma TCF12 TECextraskeletal myxoid chondrosarcoma TFE3 SFPQ, ASPSCR1, PRCC, NONO,papillary renal, alveolar soft part CLTC sarcoma, renal TFEB ALPHA renal(childhood epithelioid) TFG NTRK1, ALK papillary thyroid, ALCL, NSCLCTHRAP3 USP6 aneurysmal bone cysts TPM3 NTRK1, ALK papillary thyroid,ALCL TPR NTRK1 papillary thyroid TRIM27 RET papillary thyroid TRIM33 RETpapillary thyroid USP6 COL1A1, CDH11, ZNF9, OMD aneurysmal bone cystsZNF278 EWSR1 Ewing sarcoma ZNF331 ? follicular thyroid adenoma ZNF9 USP6aneurysmal bone cysts

TABLE 4 Exemplary selected genes associated with translocation mutationsin hematologic malignancies. Gene Hugo Gene Category TranslocationPartner Cancer Types ABL1 Priority 1 BCR, ETV6, NUP214 CML, ALL, T-ALLALK Priority 1 NPM1, TPM3, TFG, TPM4, ATIC, ALCL, NSCLC, NeuroblastomaCLTC, MSN, ALO17, CARS, EML4 BCL2 Priority 1 IGH NHL, CLL BCL6 Priority1 IG loci, ZNFN1A1, LCP1, PIM1, NHL, CLL TFRC, MHC2TA, NACA, HSPCB,HSPCA, HIST1H4I, IL21R, POU2AF1, ARHH, EIF4A2, SFRS3 CCND1 Priority 1IGH, FSTL3 CLL, B-ALL, breast CREBBP Priority 1 MLL, MORF, RUNXBP2 AL,AML FGFR1 Priority 1 BCR, FOP, ZNF198, CEP1 MPD, NHL FGFR3 Priority 1IGH, ETV6 bladder, MM, T-cell lymphoma JAK2 Priority 1 ETV6, PCM1, BCRALL, AML, MPD, CML MLL Priority 1 MLL, MLLT1, MLLT2, MLLT3, AML, ALLMLLT4, MLLT7, MLLT10, MLLT6, ELL, EPS15, AF1Q, CREBBP, SH3GL1, FNBP1,PNUTL1, MSF, GPHN, GMPS, SSH3BP1, ARHGEF12, GAS7, FOXO3A, LAF4, LCX,SEPT6, LPP, CBFA2T1, GRAF, EP300, PICALM, HEAB PDGFRA Priority 1 FIP1L1GIST, idiopathic hypereosinophilic syndrome RARA Priority 1 PML, ZNF145,TIF1, NUMA1, APL NPM1 SEPT6 MLL AML ABL2 ETV6 AML AF15Q14 MLL AML AF1QMLL ALL AF3p21 MLL ALL AF5q31 MLL ALL ALO17 ALK ALCL ARHGEF12 MLL AMLARHH BCL6 NHL ARNT ETV6 AML ATIC ALK ALCL BCL10 IGH MALT BCL11A IGHB-CLL BCL11B TLX3 T-ALL BCL3 IGH CLL BCL5 MYC CLL BCL7A MYC BNHL BCL9IGH, IGL B-ALL BCR ABL1, FGFR1, JAK2 CML, ALL, AML BIRC3 MALT1 MALT BTG1MYC BCLL CARS ALK ALCL CBFA2T1 MLL, RUNX1 AML CBFA2T3 RUNX1 AML CBFBMYH11 AML CBL MLL AML, JMML, MDS CCND2 IGL NHL, CLL CCND3 IGH MM CDK6MLLT10 ALL CDX2 ETV6 AML CEP1 FGFR1 MPD, NHL CHIC2 ETV6 AML CLTC ALK,TFE3 ALCL, renal CLTCL1 ? ALCL DDX10 NUP98 AML* DDX6 IGH B-NHL DEKNUP214 AML EIF4A2 BCL6 NHL ELF4 ERG AML ELL MLL AL ELN PAX5 B-ALL EP300MLL, RUNXBP2 colorectal, breast, pancreatic, AML EPS15 MLL ALL ERGEWSR1, TMPRSS2, ELF4, FUS, Ewing sarcoma, prostate, AML HERPUD1 ETV6NTRK3, RUNX1, PDGFRB, ABL1, congenital fibrosarcoma, multiple MN1, ABL2,FACL6, CHIC2, leukemia and lymphoma, secretory ARNT, JAK2, EVI1, CDX2,STL, breast, MDS, ALL HLXB9, MDS2, PER1, SYK, TTL, FGFR3, PAX5 EVI1RUNX1, ETV6, PRDM16, RPN1 AML, CML EWSR1 FLI1, ERG, ZNF278, NR4A3, FEV,Ewing sarcoma, desmoplastic small ATF1, ETV1, ETV4, WT1, ZNF384, roundcell tumor, ALL, clear cell CREB1, POU5F1, PBX1 sarcoma, sarcoma,myoepithelioma FACL6 ETV6 AML, AEL FCGR2B ? ALL FGFR1OP FGFR1 MPD, NHLFIP1L1 PDGFRA idiopathic hypereosinophilic syndrome FNBP1 MLL AML FOXO3AMLL AL FOXP1 PAX5 ALL FSTL3 CCND1 B-CLL FUS DDIT3, ERG, FEV, ATF1,liposarcoma, AML, Ewing sarcoma, CREB3L2 angiomatoid fibroushistiocytoma, fibromyxoid sarcoma FVT1 IGK B-NHL GAS7 MLL AML* GMPS MLLAML GPHN MLL AL GRAF MLL AML, MDS HCMOGT-1 PDGFRB JMML HEAB MLL AML HIP1PDGFRB CMML HIST1H4I BCL6 NHL HLF TCF3 ALL HLXB9 ETV6 AML HOXA11 NUP98CML HOXA13 NUP98 AML HOXA9 NUP98, MSI2 AML* HOXC11 NUP98 AML HOXC13NUP98 AML HOXD11 NUP98 AML HOXD13 NUP98 AML* HSPCA BCL6 NHL HSPCB BCL6NHL IGH MYC, FGFR3, PAX5, IRTA1, IRF4, MM, Burkitt lymphoma, NHL, CLL,CCND1, BCL9, BCL8, BCL6, BCL2, B-ALL, MALT, MLCLS BCL3, BCL10, BCL11A.LHX4, DDX6, NFKB2, PAFAH1B2, PCSK7 IGK MYC, FVT1 Burkitt lymphoma, B-NHLIGL BCL9, MYC, CCND2 Burkitt lymphoma IL2 TNFRSF17 intestinal T-celllymphoma IL21R BCL6 NHL IRF4 IGH MM IRTA1 IGH B-NHL ITK SYK peripheralT-cell lymphoma KDM5A NUP98 AML LAF4 MLL, RUNX1 ALL, T-ALL LASP1 MLL AMLLCK TRB T-ALL LCP1 BCL6 NHL LCX MLL AML LMO1 TRD T-ALL LMO2 TRD T-ALLLPP HMGA2, MLL, C12orf9 lipoma, leukemia LYL1 TRB T-ALL MAF IGH MM MAFBIGH MM MALT1 BIRC3 MALT MDS1 RUNX1 MDS, AML MDS2 ETV6 MDS MHC2TA BCL6NHL MKL1 RBM15 acute megakaryocytic leukemia MLF1 NPM1 AML MLLT1 MLL ALMLLT10 MLL, PICALM, CDK6 AL MLLT2 MLL AL MLLT3 MLL ALL MLLT4 MLL ALMLLT6 MLL AL MLLT7 MLL AL MN1 ETV6 AML, meningioma MSF MLL AML* MSI2HOXA9 CML MSN ALK ALCL MTCP1 TRA T cell prolymphocytic leukemia MUC1 IGHB-NHL MYC IGK, BCL5, BCL7A, BTG1, TRA, Burkitt lymphoma, amplified inother IGH cancers, B-CLL MYH11 CBFB AML MYH9 ALK ALCL MYST4 CREBBP AMLNACA BCL6 NHL NCOA2 RUNXBP2 AML NFKB2 IGH B-NHL NIN PDGFRB MPD NOTCH1TRB T-ALL NPM1 ALK, RARA, MLF1 NHL, APL, AML NSD1 NUP98 AML NUMA1 RARAAPL NUP214 DEK, SET, ABL1 AML, T-ALL NUP98 HOXA9, NSD1, WHSC1L1, DDX10,AML TOP1, HOXD13, PMX1, HOXA13, HOXD11, HOXA11, RAP1GDS1, HOXC11 OLIG2TRA T-ALL PAFAH1B2 IGH MLCLS PAX5 IGH, ETV6, PML, FOXP1, ZNF521, NHL,ALL, B-ALL ELN PBX1 TCF3, EWSR1 pre B-ALL, myoepithelioma PCM1 RET, JAK2papillary thyroid, CML, MPD PCSK7 IGH MLCLS PDE4DIP PDGFRB MPD PDGFRBETV6, TRIP11, HIP1, RAB5EP, H4, MPD, AML, CMML, CML NIN, HCMOGT-1,PDE4DIP PER1 ETV6 AML, CMML PICALM MLLT10, MLL TALL, AML, PIM1 BCL6 NHLPML RARA, PAX5 APL, ALL PMX1 NUP98 AML PNUTL1 MLL AML POU2AF1 BCL6 NHLPRDM16 EVI1 MDS, AML PSIP2 NUP98 AML RAB5EP PDGFRB CMML RANBP17 TRD ALLRAP1GDS1 NUP98 T-ALL RBM15 MKL1 acute megakaryocytic leukemia RPL22RUNX1 AML, CML RPN1 EVI1 AML RUNX1 RPL22, MDS1, EVI1, CBFA2T3, AML,preB-ALL, T-ALL CBFA2T1, ETV6, LAF4 RUNXBP2 CREBBP, NCOA2, EP300 AML SETNUP214 AML SFRS3 BCL6 follicular lymphoma SH3GL1 MLL AL SIL TAL1 T-ALLSSH3BP1 MLL AML STL ETV6 B-ALL SYK ETV6, ITK MDS, peripheral T-celllymphoma TAF15 TEC, CHN1, ZNF384 extraskeletal myxoid chondrosarcomas,ALL TAL1 TRD, SIL lymphoblastic leukemia/biphasic TAL2 TRB T-ALL TCF3PBX1, HLF, TFPT pre B-ALL TCL1A TRA T-CLL TCL6 TRA T-ALL TFG NTRK1, ALKpapillary thyroid, ALCL, NSCLC TFPT TCF3 pre-B ALL TFRC BCL6 NHL TIF1RARA APL TLX1 TRB, TRD T-ALL TLX3 BCL11B T-ALL TNFRSF17 IL2 intestinalT-cell lymphoma TOP1 NUP98 AML* TPM3 NTRK1, ALK papillary thyroid, ALCLTPM4 ALK ALCL TRA ATL, OLIG2, MYC, TCL1A, TCL6, T-ALL MTCP1, TCL6 TRBHOX11, LCK, NOTCH1, TAL2, T-ALL LYL1 TRD TAL1, HOX11, TLX1, LMO1, T-cellleukemia LMO2, RANBP17 TRIP11 PDGFRB AML TTL ETV6 ALL WHSC1 IGH MMWHSC1L1 NUP98 AML ZNF145 RARA APL ZNF198 FGFR1 MPD, NHL ZNF384 EWSR1,TAF15 ALL ZNF521 PAX5 ALL ZNFN1A1 BCL6 ALL, DLBL

Example G: Exemplary Bait Sequences for Hybrid Capture

Table 7 provides exemplary baits for three targets: SMAD3_target_10,SMAD3_target_11, SMAD3_target_12.

TABLE 7 Exemplary Baits  1. Gene Target Bait genomic location SMAD3SMAD3_target_10 chr15: 67477013-67477132CCATTGTGTGTGAGCAAAGGCACCCTGTCCAGTCTAACCTGAATCTCTGTAGGAAGAGGCGTGCGGCTCTACTACATCGGAGGGGAGGTCTTCGCAGAGTGCCTCAGTGACAGCGCTATT (SEQ ID NO: 37) (Bait ID: SMAD3_target_10.2)  2. Gene TargetBait genomic location SMAD3 SMAD3_target_10 chr15: 67477037-67477156CTGTCCAGTCTAACCTGAATCTCTGTAGGAAGAGGCGTGCGGCTCTACTACATCGGAGGGGAGGTCTTCGCAGAGTGCCTCAGTGACAGCGCTATTTTTGTCCAGTCTCCCAACTGTAAC (SEQ ID NO: 38) (Bait ID: SMAD3_target_10.4)  3. Gene TargetBait genomic location SMAD3 SMAD3_target_10 chr15: 67477061-67477180GTAGGAAGAGGCGTGCGGCTCTACTACATCGGAGGGGAGGTCTTCGCAGAGTGCCTCAGTGACAGCGCTATTTTTGTCCAGTCTCCCAACTGTAACCAGCGCTATGGCTGGCACCCGGCC (SEQ ID NO: 39) (Bait ID: SMAD3_target_10.6)  4. Gene TargetBait genomic location SMAD3 SMAD3_target_10 chr15: 67477085-67477204TACATCGGAGGGGAGGTCTTCGCAGAGTGCCTCAGTGACAGCGCTATTTTTGTCCAGTCTCCCAACTGTAACCAGCGCTATGGCTGGCACCCGGCCACCGTCTGCAAGATCCCACCAGGT (SEQ ID NO: 40) (Bait ID: SMAD3_target_10.1)  5. Gene TargetBait genomic location SMAD3 SMAD3_target_10 chr15: 67477109-67477228GAGTGCCTCAGTGACAGCGCTATTTTTGTCCAGTCTCCCAACTGTAACCAGCGCTATGGCTGGCACCCGGCCACCGTCTGCAAGATCCCACCAGGTAAACGAGCCGCACAGGCACCCCTG (SEQ ID NO: 41) (Bait ID: SMAD3_target_10.5)  6. Gene TargetBait genomic location SMAD3 SMAD3_target_10 chr15: 67477133-67477252TTTGTCCAGTCTCCCAACTGTAACCAGCGCTATGGCTGGCACCCGGCCACCGTCTGCAAGATCCCACCAGGTAAACGAGCCGCACAGGCACCCCTGCCTTGAGGTCCCTCTCCGAGTGCA (SEQ ID NO: 142) (Bait ID: SMAD3_target_10.3)  7. GeneTarget Bait genomic location SMAD3 SMAD3_target_11chr15: 67479655-67479774GACCTGGCCACTTCCATCCCCACAGCCCTGTTTCTGTGTTTTTGGCAGGATGCAACCTGAAGATCTTCAACAACCAGGAGTTCGCTGCCCTCCTGGCCCAGTCGGTCAACCAGGGCTTTG (SEQ ID NO: 43) (Bait ID: SMAD3_target_11.1)  8. Gene TargetBait genomic location SMAD3 SMAD3_target_11 chr15: 67479679-67479798GCCCTGTTTCTGTGTTTTTGGCAGGATGCAACCTGAAGATCTTCAACAACCAGGAGTTCGCTGCCCTCCTGGCCCAGTCGGTCAACCAGGGCTTTGAGGCTGTCTACCAGTTGACCCGAA (SEQ ID NO: 44) (Bait ID: SMAD3_target_11.5)  9. Gene TargetBait genomic location SMAD3 SMAD3_target_11 chr15: 67479703-67479822GATGCAACCTGAAGATCTTCAACAACCAGGAGTTCGCTGCCCTCCTGGCCCAGTCGGTCAACCAGGGCTTTGAGGCTGTCTACCAGTTGACCCGAATGTGCACCATCCGCATGAGCTTCG (SEQ ID NO: 45) (Bait ID: SMAD3_target_11.3) 10. Gene TargetBait genomic location SMAD3 SMAD3_target_11 chr15: 67479727-67479846ACCAGGAGTTCGCTGCCCTCCTGGCCCAGTCGGTCAACCAGGGCTTTGAGGCTGTCTACCAGTTGACCCGAATGTGCACCATCCGCATGAGCTTCGTCAAAGGCTGGGGAGCGGAGTACA (SEQ ID NO46) (Bait ID: SMAD3_target_11.4) 11. Gene TargetBait genomic location SMAD3 SMAD3_target_11 chr15: 67479751-67479870CCCAGTCGGTCAACCAGGGCTTTGAGGCTGTCTACCAGTTGACCCGAATGTGCACCATCCGCATGAGCTTCGTCAAAGGCTGGGGAGCGGAGTACAGGTCAGTTATGGGTGCTGCCTACA (SEQ ID NO: 47) (Bait ID: SMAD3_target_11.2) 12. GeneTarget Bait genomic location SMAD3 SMAD3_target_11chr15: 67479775-67479894AGGCTGTCTACCAGTTGACCCGAATGTGCACCATCCGCATGAGCTTCGTCAAAGGCTGGGGAGCGGAGTACAGGTCAGTTATGGGTGCTGCCTACATCAGGGGACCCAACTCCAGGTGAC (SEQ ID NO: 48) (Bait ID: SMAD3_target_11.6) 13. GeneTarget Bait genomic location SMAD3 SMAD3_target_12chr15: 67482692-67482811TGTAACCCCCTGGAGATTTTTTAAGTCCCCCACCCCACCCCTTTCCCTATTTCTTACAGGAGACAGACTGTGACCAGTACCCCCTGCTGGATTGAGCTGCACCTGAATGGGCCTTTGCAG (SEQ ID NO: 49) (Bait ID: SMAD3_target_12.5) 14. Gene TargetBait genomic location SMAD3 SMAD3_target_12 chr15: 67482716-67482835GTCCCCCACCCCACCCCTTTCCCTATTTCTTACAGGAGACAGACTGTGACCAGTACCCCCTGCTGGATTGAGCTGCACCTGAATGGGCCTTTGCAGTGGCTTGACAAGGTCCTCACCCAG (SEQ ID NO: 50) (Bait ID: SMAD3_target_12.3) 15. Gene TargetBait genomic location SMAD3 SMAD3_target_12 chr15: 67482740-67482859ATTTCTTACAGGAGACAGACTGTGACCAGTACCCCCTGCTGGATTGAGCTGCACCTGAATGGGCCTTTGCAGTGGCTTGACAAGGTCCTCACCCAGATGGGCTCCCCAAGCATCCGCTGT (SEQ ID NO: 51) (Bait ID: SMAD3_target_12.2) 16. Gene TargetBait genomic location SMAD3 SMAD3_target_12 chr15: 67482764-67482883ACCAGTACCCCCTGCTGGATTGAGCTGCACCTGAATGGGCCTTTGCAGTGGCTTGACAAGGTCCTCACCCAGATGGGCTCCCCAAGCATCCGCTGTTCCAGTGTGTCTTAGAGACATCAA (SEQ ID NO: 52) (Bait ID: SMAD3_target_12.4) 17. Gene TargetBait genomic location SMAD3 SMAD3_target_12 chr15: 67482788-67482907CTGCACCTGAATGGGCCTTTGCAGTGGCTTGACAAGGTCCTCACCCAGATGGGCTCCCCAAGCATCCGCTGTTCCAGTGTGTCTTAGAGACATCAAGTATGGTAGGGGAGGGCAGGCTTG (SEQ ID NO: 53) (Bait ID: SMAD3_target_12.6) 18. Gene TargetBait genomic location SMAD3 SMAD3_target_12 chr15: 67482812-67482931TGGCTTGACAAGGTCCTCACCCAGATGGGCTCCCCAAGCATCCGCTGTTCCAGTGTGTCTTAGAGACATCAAGTATGGTAGGGGAGGGCAGGCTTGGGGAAAATGGCCATGCAGGAGGTG (SEQ ID NO: 54) (Bait ID: SMAD3_target_12.1)

Table 8 provides baits with sequences for two targets: FLT3_target_24modified to reduce the secondary structure. FLT4_target_31 has somearbitrary sequence on both ends of the baits which is effectivelysimilar to a shorter bait. Both improve coverage by about 4× (˜4×improvement in coverage).

TABLE 8 Exemplary Baits  1. Gene Target Bait genomic location FLT3FLT3_target_24 chr13: 28674626-28674745 Original sequenceCGTCGCGCGCCAACGCCGGCATGGCCTCCGGAGCCCGGGGTCCCCAGGCCGCGCCGGCCCAGCCCTGCGATGCCGCCTGGAGCGGCGCGCCTCGCGCTGCAGGTGGCTCTCTTAAGGATG (SEQ ID NO: 55) Modified sequenceCGTCTCACGCCAACGCAAGCATGTCCTCCGGAGCCCGGGGTCCCCAGGCCGCGCCGGCCCAGCCCTGCGATGCCGCCTGGAGCGGCGCGCCTCGCACTGCAGATGGCTCTCTTAAGGATG (SEQ ID NO: 56) (Bait ID: FLT3_target_24.1)  2. Gene TargetBait genomic location FLT3 FLT3_target_24 chr13: 28674602-28674721Original sequence TACCGAGCAGCGGCAGCTGGCCGCCGTCGCGCGCCAACGCCGGCATGGCCTCCGGAGCCCGGGGTCCCCAGGCCGCGCCGGCCCAGCCCTGCGATGCCGCCTGGAGCGGCGCGCCTCGCG (SEQ ID NO: 57) Modified sequenceTACCGAGCAGCGGCAGCTGGCCGCCGTCGCGCGCCAACGCCGGCATGGCCTCCGGAGCCCGGGGTCCCCAGGCCGCGCATGCCCAGCCCTGCGATGCCGCCTTGAGCAACGCGCCTCACG (SEQ ID NO: 58) (Bait ID: FLT3_target_24.2)  3. Gene TargetBait genomic location FLT3 FLT3_target_24 chr13: 28674578-28674697Original sequence GCTGCGAGCGAGCGAGCGGGGCCTTACCGAGCAGCGGCAGCTGGCCGCCGTCGCGCGCCAACGCCGGCATGGCCTCCGGAGCCCGGGGTCCCCAGGCCGCGCCGGCCCAGCCCTGCGATG (SEQ ID NO: 59) Modified sequenceGCTTCGAGAGAGCGAGCGGGGCCTTACCGAGCAGCAGCAGCTGGCCGCCGTCGCGCGCCAACGCCGGCATGGCCTCCGGAGCCCGGGGTCCCCAGGCCGCGCCAGCCCAGCCCTGAGATG (SEQ ID NO: 60) (Bait ID: FLT3_target_24.3)  4. Gene TargetBait genomic location FLT3 FLT3_target_24 chr13: 28674554-28674673Original sequence GTGGGGGCTGAGGGACCGCGAGGGGCTGCGAGCGAGCGAGCGGGGCCTTACCGAGCAGCGGCAGCTGGCCGCCGTCGCGCGCCAACGCCGGCATGGCCTCCGGAGCCCGGGGTCCCCAGG (SEQ ID NO: 61) Modified sequenceGAGGTGGCTGAGAGACCGCGAGGAGCTGCGAGCGAGCGAGCGGGGCCTTACCGAGCAGCGGCAGCTGGCCGCCGTCGCGCGCCAACGCAGGCATGGCCTCCGGAGCCCAGGGTCCCCAGG (SEQ ID NO: 62) (Bait ID: FLT3_target_24.4)  5. GeneTarget Bait genomic location FLT3 FLT3_target_24chr13: 28674506-28674625 Original sequenceCGAGGCGGCTGGGCCGGAGGAGGCGCGCGCCCGGGTCCACACTGCGGGGTGGGGGCTGAGGGACCGCGAGGGGCTGCGAGCGAGCGAGCGGGGCCTTACCGAGCAGCGGCAGCTGGCCGC (SEQ ID NO: 63) Modified sequenceCGAGGCGGCTGGGCCGGAGGAGGCGCGCGCCCGGATCCACACTGCGGGGTGGGGGCTGAGGGACCGCGAGGGGCTGCGAGCGAGCGAGCGGGGACTTACCGAGCAGCGGCAACTGGACGC (SEQ ID NO: 64) (Bait ID: FLT3_target_24.5)  6. GeneTarget Bait genomic location FLT3 FLT3_target_24chr13: 28674530-28674649 Original sequenceGCGCGCCCGGGTCCACACTGCGGGGTGGGGGCTGAGGGACCGCGAGGGGCTGCGAGCGAGCGAGCGGGGCCTTACCGAGCAGCGGCAGCTGGCCGCCGTCGCGCGCCAACGCCGGCATGG (SEQ ID NO: 65) Modified sequenceGCACGCACGGATCCACACTGCGGGGTGGGGGCTGAGGGACCGCGAGGAGCTGCGAGCGAGCGAGCGGGGCCTTACCGAGCAGCGGCAGCTGGCAGCCGTCGCGCGCCAACGCCGGCATGG (SEQ ID NO: 66) (Bait ID: FLT3_target_24.6)  7. GeneTarget Bait genomic location FLT4 FLT4_target_31chr5: 180076516-180076635 Original sequenceTCGCAGGCACAGCGCGGCGCCCCGCTGCATCTCCGGCCGCTGCGCGTGGGTCCGACCCGAGCGGCCGCGGCTCGGGGCTGAAAGTGTCCGCGCGGGCGCCGGCTGGCCTGGGGCGGGGCG (SEQ ID NO: 67) Modified sequenceCACACACACAAGCGCGGCGCCCCGCTGCATCTCCGGCCGCTGCGCGTGGGTCCGACCCGAGCGGCCGCGGCTCGGGGCTGAAAGTGTCCGCGCGGGCGCCGGCTGGCCTGCACACACACA (SEQ ID NO: 68) (Bait ID: FLT4_target_31.1)  8. Gene TargetBait genomic location FLT4 FLT4_target_31 chr5: 180076396-180076515Original sequence GGCGGAGCGGTCTCAGCGCCCGCCCCAGGTGCGCGGTACCCCCTCCCCGGCCAGCCCCACGCTCGGGCGGGTGGCCCGTTCGCCGCGCTCACCGTCCAGGAGTCCCAGGCAGAGCCACAG (SEQ ID NO: 69) Modified sequenceCACACACACATCTCAGCGCCCGCCCCAGGTGCGCGGTACCCCCTCCCCGGCCAGCCCCACGCTCGGGCGGGTGGCCCGTTCGCCGCGCTCACCGTCCAGGAGTCCCAGGCCACACACACA (SEQ ID NO: 70) (Bait ID: FLT4_target_31.2)  9. Gene TargetBait genomic location FLT4 FLT4_target_31 chr5: 180076420-180076539Original sequence CCAGGTGCGCGGTACCCCCTCCCCGGCCAGCCCCACGCTCGGGCGGGTGGCCCGTTCGCCGCGCTCACCGTCCAGGAGTCCCAGGCAGAGCCACAGTCGCAGGCACAGCGCGGCGCCCCG (SEQ ID NO: 71) Modified sequenceCACACACACAGGTACCCCCTCCCCGGCCAGCCCCACGCTCGGGCGGGTGGCCCGTTCGCCGCGCTCACCGTCCAGGAGTCCCAGGCAGAGCCACAGTCGCAGGCACAGCGCACACACACA (SEQ ID NO: 72) (Bait ID: FLT4_target_31.3) 10. Gene TargetBait genomic location FLT4 FLT4_target_31 chr5: 180076468-180076587Original sequence GGCCCGTTCGCCGCGCTCACCGTCCAGGAGTCCCAGGCAGAGCCACAGTCGCAGGCACAGCGCGGCGCCCCGCTGCATCTCCGGCCGCTGCGCGTGGGTCCGACCCGAGCGGCCGCGGCT (SEQ ID NO: 73) Modified sequenceCACACACACACCGCGCTCACCGTCCAGGAGTCCCAGGCAGAGCCACAGTCGCAGGCACAGCGCGGCGCCCCGCTGCATCTCCGGCCGCTGCGCGTGGGTCCGACCCGAGCCACACACACA (SEQ ID NO: 74) (Bait ID: FLT4_target_31.4) 11. Gene TargetBait genomic location FLT4 FLT4_target_31 chr5: 180076444-180076563Original sequence GGCCAGCCCCACGCTCGGGCGGGTGGCCCGTTCGCCGCGCTCACCGTCCAGGAGTCCCAGGCAGAGCCACAGTCGCAGGCACAGCGCGGCGCCCCGCTGCATCTCCGGCCGCTGCGCGTG (SEQ ID NO: 75) Modified sequenceCACACACACAACGCTCGGGCGGGTGGCCCGTTCGCCGCGCTCACCGTCCAGGAGTCCCAGGCAGAGCCACAGTCGCAGGCACAGCGCGGCGCCCCGCTGCATCTCCGGCCCACACACACA (SEQ ID NO: 76) (Bait ID: FLT4_target_31.5) 12. Gene TargetBait genomic location FLT4 FLT4_target_31 chr5: 180076492-180076611Original sequence CAGGAGTCCCAGGCAGAGCCACAGTCGCAGGCACAGCGCGGCGCCCCGCTGCATCTCCGGCCGCTGCGCGTGGGTCCGACCCGAGCGGCCGCGGCTCGGGGCTGAAAGTGTCCGCGCGGG (SEQ ID NO: 77) Modified sequenceCACACACACAAGGCAGAGCCACAGTCGCAGGCACAGCGCGGCGCCCCGCTGCATCTCCGGCCGCTGCGCGTGGGTCCGACCCGAGCGGCCGCGGCTCGGGGCTGAAAGTGCACACACACA (SEQ ID NO: 78) (Bait ID: FLT4_target_31.6)

Example H: A Bayesian Approach for Sensitive Detection of SomaticGenomic Alterations from Next-Generation Sequencing of Clinical CancerSpecimens

The Bayesian approach described herein was implemented in the followingexamples.

The utility of this approach is illustrated by power calculationsdescribing the impact of data-driven priors on substitution detection inthe lower range of mutation frequencies relevant in the clinicalsetting. As shown in FIG. 4, the values of prior expectation (forexample, 1e-6 or 10% prior) and mutation frequency (for example, 1%, 5%,or 15% mutation) correspond to the values described in (i) and (ii) of“A Bayesian Approach for Sensitive Detection of Somatic GenomicAlterations from Next-generation Sequencing of Clinical CancerSpecimens,” respectively. FIG. 4 shows that incorporating priorexpectations can improve detection power for rarer mutations, forexample, by reducing the required coverage depth at mutated sites, orincreasing the estimated power (sensitivity) to detect mutations.

Example I: A Bayesian Approach: Application to a Constructed Low PurityMulti-clonal Sample

To further demonstrate these benefits of the Bayesian approach disclosedherein, an artificial low-purity, multi-clonal “tumor” sample wasconstructed by equal admixture of DNA from 10 participants in the 1000Genomes project, thereby creating a DNA pool containing a large numberof sequence variants present at ˜5% or 10% of the total DNA (arisingfrom private heterozygous SNPs). The mix was subjected to hybridselection for exons of 182 cancer-related genes and sequenced on theIllumina HiSeq2000 platform, yielding an average coverage ofapproximately 350× across the gene panel. Each constituent sample waslikewise processed individually to determine genotype at all SNP sites.Of the approximately 260 ˜5% “mutations” present in the pool, 89% weredetected with high-confidence using a prior of 1e-6, whereas 94% and 95%were detectable using a prior of 1% and 10% (average coverage of missedsites ˜125×), respectively, supporting the theoretical conclusionsabove. Of the 102 10% “mutations” present in the pool, 98% were detectedwith high-confidence using a prior of le-6, whereas 99% and 99% weredetectable using a prior of 1% and 10% (coverage of missed site 13×).

Example J: A Bayesian Approach: Application to Lung and Colon TumorSamples

Prior expectations of the frequency of relevant mutations in severalcancer types from the COSMIC database (on the worldwide web atsanger.ac.uk/genetics/CGP/cosmic) were derived and analyzed more than 80lung and colon cancer samples extracted from routine clinical specimens.Known mutations in more than 20 different genes were observed, includinga 1% PIK3CA mutation p.H1047R in a colon cancer that could only bedetected by incorporation of the 3% prior for this mutation in thiscancer type. These results show that judicious incorporation of priorexpectations around tumor type specific mutation spectra can bebeneficial in translation of NGS-based tumor genome analysis to theclinical setting.

Example K: A Bayesian Approach: Application to Breast Cancer Samples

Substitution mutation calling in exons of 182 cancer-related genessequenced to ˜260× for an FFPE breast cancer samples was performed. Thenumber of sites with >2 copies of an alternate allele is 1,793. Thenumber of sites with >99% posterior belief in presence of mutation is402. The number of sites remaining after filters is 188, which isapproximately the expected number of variant sites. The number of sitesthat are not in dbSNP is 14, which is approximately the expected numberof sites not in dbSNP as dbSNP captures >90% of variation. The number ofnon-synonymous sites is 5. The number of sites in COSMIC is 2 (PIK3CAp.H1047R and P53 p.F113S).

Example L: A Bayesian Approach: Detection of Infrequent Mutations

Many routine clinical specimens contain relevant rare mutations. FIG. 5shows mutation frequencies in more than 100 clinical cancer samples.Samples were FFPE biopsies, surgical resections, or fine-needleaspirates of predominantly colon and lung cancers. The frequencyspectrum of known mutations found in a series of clinical sample is showin Table 12.

TABLE 12 Frequency spectrum of known mutations found in a series ofclinical samples Frequency spectrum of known mutations found in a seriesof clinical samples Fraction of Fraction of Fraction of Fraction ofFraction of mutation mutation mutation mutation mutation <5% <10% <25%<50% <100% 7%* 17% 50% 85% 100% * likely underestimated

Example M.1. High Performance Solution-Based Target Selection UsingIndividually Synthesized Oligonucleotide Capture Probes

The availability of solution-based genomic target selection techniqueshas enabled rapid development of targeted sequencing applications, someof which have led to the introduction of clinical sequencing tests.Commercialized hybridization capture reagents are based onarray-synthesized oligonucleotides, which are converted to biotinylatedDNA or RNA probes (“baits”). However, methods of generating thesecomplex pools of probes face performance challenges, for examplecapturing high-GC content targets.

An alternative approach using individually synthesized, 5′-biotinylatedoligonucleotides (“oligo-baits”) for capturing a target region of ˜130kb representing 57 clinically relevant and actionable cancer-relatedgenes is described herein. Indexed sequencing libraries selected usingthese oligo-baits with a 24-hour hybridization procedure yielded5,000-fold target enrichment. 50M 49×49 paired-end reads generated anaverage target coverage of 2100× with a standard deviation of 568×(27%). All targets were covered successfully, with 99.95% of thetargeted bases covered at >500x. Furthermore, the target coverage hadvirtually no GC-bias. Targets with GC content >70% averaged 1,975xcoverage, and targets with GC content <35% averaged 1,996× coverage.

High performance was retained using even shorter hybridization times:99.3% of targeted bases were covered at >500× after a 2.5 hourhybridization.

Use of SSPE (Salmon Sperm, PE)/Denhardt's outperformed hyb/wash bufferscontaining TEACl, TMACl, and/or dextran sulfate.

Oligo-baits can be spiked into array-derived bait pools to increase thecoverage of otherwise difficult to capture (for example, high % GC)regions, or to rapidly add new gene content. This approach offers ahighly effective and scalable method for developing high performancetargeted clinical sequencing tests.

Example M.2: Method of Optimizing Capture Baits

Three bait sets were tested. The results are summarized in FIG. 7. Thebait sets were as follows:

Bait set #1 consists of 5′-biotinylated, individually synthesized DNAoligonucleotide baits only.

Bait set #2 includes biotinylated, array-derived RNA baits spiked with5′-biotinylated, individually synthesized DNA oligonucleotide baits.

Bait set #3 consists of biotinylated, array-derived RNA baits only.

All 5′-biotinylated, individually synthesized DNA oligonucleotide were120 bases with a 5′ biotin.

FIG. 7 is a coverage histogram comparing the uniformity in coveragedetected with Bait set #1 and Bait set #2, compared to Bait set #3. Thebait sets are shown as #1, 2, and 3 in FIG. 7. Several gaps in coveragewere present using Bait set #3 corresponding to high % GC, whereas thecorresponding regions were deeply covered using Bait sets #1 and #2, asdepicted in FIG. 7. In FIG. 7, the left-hand panel labeled“GC_density_target . . . ” indicates the local GC content within thetarget, The line represents 65% GC content, where any values above theline represent a higher GC content. As shown in the histogram, thecoverage is the lowest for Bait set #3 in areas of high GC content. Thebottom panel in FIG. 7 labeled “IDT_baits . . . ” indicates theplacement of the oligos covering the target shown.

A graphic representation of the changes in the number of targets andcoverage using array-derived bait sets alone or spiked withindividually-synthesized baits is depicted in FIG. 6. More specifically,FIG. 6 is a linear representation of a coverage histogram. The number oftargets (y-axis) are depicted as a function of coverage (x-axis). Line#1 represents the coverage using a bait set that includes5′-biotinylated, array-derived RNA oligonucleotide baits spiked with5′-biotinylated, individually synthesized DNA oligonucleotide baits(referred to in FIG. 6 as “Bait set #1”). Line #2 represents thecoverage obtained using a bait set that includes biotinylated,array-derived RNA oligonucleotide baits only (referred to in FIG. 6 as“Bait set #2”). The overall average coverage using Bait set #2 was 924,whereas the coverage in areas of high GC content (about 68%) using Baitset #2 was 73. In contrast, when Bait set #1 was used, the overallcoverage was similar to Bait Set #1, about 918, but the coverage wasimproved to 183 in areas of high GC content.

Example M.3: Exemplary Experimental Conditions for Evaluating Bait Sets

Bait set A consists of 5′-biotinylated, individually synthesized DNAoligonucleotide baits only. The original set was 1000 oligos, covering133 kb of target territory (referred to herein as “the large set,” “Baitset A” or “DNA oligo baits”).

For the “spike-in” experiments, the original 1000 DNA oligo set (“thelarge set”) was added to a bait set consisting of biotinylated,array-derived RNA oligonucleotide baits (referred to in this example as“Bait set B” or “RNA baits”). Different ratios of DNA oligo baits fromBait set A were mixed with RNA baits from Bait set B. In particular, aDNA oligo bait:RNA bait ratio of 1:10 was used (10 ng total DNA oligobaits to 100 ng total RNA baits). Hybridization and washing conditionswere matched to those that are most ideal for the RNA baits.

With low tiling densities, strong periodicities in coverage weredetected when using DNA oligo baits that corresponded to bait placement.In addition, low tiling densities may make capturing of alleles withindels more difficult. Therefore, bait sets were designed for MAP3K1with the different tiling densities depicted in Table 13. In the belowmixes, Mix 1 containing 5′-biotinylated, individually synthesized DNAoligo baits designed to capture the exons of six cancer-relevant genes(DAXX, TRRAP, CREBBP, GRIN2A, SPOP, GNA11) were spiked into thearray-derived RNA oligonucleotide baits only (Bait set B). DAXX, TRRAP,CREBBP, GRIN2A, and SPOP were not present in the RNA bait set. Mixes 2-4were spiked into Bait Set A (the large set of DNA oligo baits) to testdifferent tiling densities (with Mix 2 being the densest) of capturebaits for the exons of MAP3K1. The RNA bait set alone covered about 1 MBof sequence.

TABLE 13 Mixes for methods using capture probes Category Number Mix 1369 oligos to melanoma genes Mix 2 91 oligos tiling density of 60 toMAP3K1 Mix 3 57 oligos tiling density of 100 to MAP3K1 Mix 4 40 oligostiling density of 150 toMAP3K1 Mix 5 3 oligos to STK11 exon 3

Input into capture was 2 μg of pooled cell-line DNA libraries. 2 μglibrary was mixed with blocking mix (Table 14), dried down, andresuspended in 9 μl water. This mixture was then put in a plate,transferred to a cycler, and run at 98° C. for 5 minutes, followed by68° C. for 2 minutes. The plate was then unsealed, and 11 μL DNAbait/hyb buffer mixture @ 68° C. was added. The DNA bait/hyb mixture at68° C.=10 μL hyb buffer+1 μL bait (containing 10 ng, 50 ng, or 100 ngbait).

For captures with DNA baits alone (for example, Bait set A),hybridization was performed at 68° C., and washes were performed. Baitswere tested at 5 ng, 10 ng, 100 ng, 1000 ng, and 2000 ng (per 2 μg inputlibrary). For 24 hr. hybs, the 5-10 ng conditions, and up to 100 ngconditions were tested.

For captures with the large DNA bait set (100 kb) spiked into theRNA-array bait set (B) to rescue poor performing/high GC regions,hybridization was performed at 68° C., and washes were performed at 70°C. Bait sets were tested at 1:10 DNA oligo: RNA baits (that is, 10 ngtotal mass of oligo baits, and 100 ng total mass of RNA baits).

For captures with the small, gene focused DNA bait set spiked into theRNA bait set, hybridization was performed at 68° C., and a range of washtemperatures were tested (62° C., 64° C., 66° C., 68° C., 70° C., and72° C.).

Mix 1 (adding 6 new genes) was tested at the following ratios: 1:5, 1:10and 1:20 total oligo DNA bait mass: RNA bait mass (that is, 20 ng:100ng, 10 ng:100 ng, and 5 ng:100 ng).

Mix 5 (3 oligos representing exon 3 of STK11 to path low coverage) wastested at 1:500, 1:1000, and 1:2000 DNA oligo:RNA oligo. 100 ng of totalRNA baits were used. STK11 was tested as it represents an importantcancer target with poor detection performance when captured with the RNAbaits alone. DNA oligo spiking of exon 3 of STK11 boosts coverage froman average of 70× to 300×.

TABLE 14 Buffers for methods using capture probes Baits (pooled IDT39600 100 nmol = 0.0039600 grams = oligos) (g/mol) 3,960,000 nanogramsResuspended in low 25 mL 250 μL Tris TE 5 μL EDTA Blocking Mix [Stock][Working] 14.5 μl/rxn Cot1 1 μg/μl 1 μg/μl 10 Salmon Sperm 10 μg/μl 10.0μg/μl 1 PE 1.0 800 μM 800 μM 1.75 Universal Index 800 μM 800 μM 1.75 2XHyb Buffer [Stock] [Final] in 10 ml (10 μl/rxn) SSPE 20X 10X 5 mlDenhardt's 50X 10X 2 ml EDTA 0.5M 0.01M 200 μl SDS 10% 0.20% 200 μlWater 2.6 ml Bead Wash [Stock] [Final] in 50 ml (200 μl/wash) NaCl 5M 1M10 ml Tris 1M 10 mM 500 μl EDTA   0.5M  1 mM 100 μl Water 39.4 ml WashBuffer 1 [Stock] [Final] in 50 ml (150 μl/wash) SSC 20X 1X 2.5 ml SDS10% 0.10% 500 μl Water 47 ml Wash Buffer 2 [Stock] [Final] in 50 ml (150μl/wash) SSC 20X 0.1X 250 μl SDS 10% 0.10% 500 μl Water 49.25 ml

Example N: Reducing Off-Target Nucleic Acid Binding of Library Members

Off-target nucleic acid interactions can limit the efficiency of theselection of target nucleic acids by hybridization (for example,solution or solid-phase hybridization) to a capture probe, for example,an oligonucleotide bait. Off-target selection is typically increasedwhen the stringency conditions for hybrid selection are reduced, forexample, when selecting for a target:capture duplex having a lowernucleic acid melting temperature (for example, T_(m) of DNA:DNA duplexesas compared to RNA:DNA duplexes). Thus, capture of off-target sequencecan be more problematic in DNA:DNA hybridizations. Off-target selectioncan result, for example, in one or more of decreased yields ofhybridization capture and/or artifactual hybrid capture, which in turnlead to inefficiencies in subsequent steps, for example, sequencing.

Library members can include a library insert (which, if on-target, formsa duplex with the capture probe, for example, a bait) and one or morenon-target sequences (for example, one or more of adaptor sequences,amplification primers or tags, and bar code tags). Typically, a baithybridizes to the library insert, for example, a target DNA. However,the library insert can have universal adaptors, which are typicallypresent on every fragment in the library. The non-target sequence of thecapture probe-hybridized library member, can, by duplex formation withother sequences in the reaction mixture (for example, via binding toadaptor sequences), lead to the selection of undesired sequences, forexample, off-target library members.

While not wishing to be bound by theory, concatenation between anon-target library member that has formed a duplex with the capture probeand off-target sequences can result in selection of off-targetsequences. FIG. 6 illustrates in diagram form an exemplary configurationof non-target concatemers of the library members. The non-target regions(for example, adaptors depicted as “P5” and “P7”) are shown ashybridizing to their complementary non-target strands (depicted as“rcP5” and “rcP7,” respectively). A biotin-tagged bait is shownhybridizing to a complementary region of the target insert of thelibrary member. Off-target binding can lead to a concatenation oflibrary members, thus leading to a reduction in target-bindingspecificity (also referred to herein as increased off-target selection).

In target:capture duplexes involving DNA (library member):RNA (bait)duplexes, concatenation between an on-target library member that hasformed a duplex with the capture probe and off-target sequences can bebroken up during high stringency washes typically performed at 65-70° C.Typically, washes involving lower melting of DNA:DNA duplexes areperformed at lower temperatures relative to RNA:DNA duplexes. Theinability to break up the concatenation has kept the percentage oftarget capture relatively low when using DNA Baits (45-50%).Commercially available blocking oligos complementary to adaptors areadded to minimize the concatenation, but they typically do notadequately inhibit chain formation, particularly in DNA:DNAhybridizations.

Methods and compositions are disclosed herein that reduce non-targetsequence (for example, adaptor)-mediated selection. In certainembodiments, blocking oligonucleotides are disclosed that arecomplementary to, or can form a duplex with, the non-target nucleic acidsequence of the library member (for example, an adaptor sequence), andhave a value for a parameter related to the binding interaction betweenthe blocking oligonucleotide and the non-target nucleic acid sequence ofthe library member that is higher than the value for the non-targetnucleic acid sequence to a background nucleic acid, for example, othercomplementary non-target nucleic acid sequences. Exemplary blockingoligonucleotides having an increased binding interaction includeoligonucleotides having extended blocker length, for example, extendedcomplementarity to a non-target nucleic acid; blocking oligonucleotideshaving one or more non-naturally-occurring nucleotides; and blockingoligonucleotides that include (or a substantially composed of)oligoribonucleotides, instead of deoxyribonucleotides.

Example O: Extended Blocker Length

This Example demonstrates that percent on-target selection can beimproved by extending the length of the blocking oligonucleotide.

Adaptor-specific blocking oligonucleotides are added to thehybridization reaction performed as described herein to preventcarryover of off-target nucleic acid binding as described in Example 14.In the experimental conditions described in Example 4, high stringencywashes are performed, which are likely to denature off-target binding.However, optimal hybridization and washing conditions for DNA:DNAinteractions lower the temperatures of the washes as described inExamples 13A-13C, thus increasing off-target binding.

Blocking oligos can be designed complementary to the adaptors, forexample, the Illumina multiplex adaptors described in Example 3, toincrease the extent of complementarity between the adaptor and theblocking oligo. For example, the P5 blocking oligo is 58 bp bases inlength, but the blocker is only 46 bases. The length of the P5 blockingoligo was extended by 19 bases. Extending the length of the blockingoligo by 19 bases increased selection efficiency by approximately 5%(shown in FIG. 9). FIG. 9 is a bar graph depicting the percentage oftarget selection using standard and extended blocking oligos. Data fromfour representative experiments are shown. FIG. 10 depicts an exoncoverage histogram showing capture results using standard or extendedblockers.

Improved blocking can be achieved by extending the length of thecomplementarity region between the adaptor and the blocking oligo, thusincreasing the melting temperature.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned herein arehereby incorporated by reference in their entirety as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated by reference. In case ofconflict, the present application, including any definitions herein,will control.

Also incorporated by reference in their entirety are any polynucleotideand polypeptide sequences which reference an accession numbercorrelating to an entry in a public database, such as those maintainedby The Institute for Genomic Research (TIGR) on the world wide web attigr.org and/or the National Center for Biotechnology Information (NCBI)on the world wide web at ncbi.nlm.nih.gov.

The terminology used herein is for the purpose of describing particularembodiments only, and is not intended to be limiting. With respect tothe use of substantially, any plural and/or singular terms herein, thosehaving skill in the art can translate from the plural as is appropriateto the context and/or application. The various singular/pluralpermutations may be expressly set forth herein for the sake of clarity.

While the present invention has been described with reference to certainembodiments, it will be understood by those skilled in the art thatvarious changes may be made and equivalents may be substituted withoutdeparting from the scope of the present invention. In addition, manymodifications may be made to adapt a particular situation or material tothe teachings of the present invention without departing from its scope.Therefore, it is intended that the present invention not be limited tothe particular embodiments or examples disclosed, but that the presentinvention will include all embodiments falling within the scope of theappended claims.

1-24. (canceled)
 25. A method of selecting a desired template nucleicacid from a population of template nucleic acids, comprising: (a)contacting the population of template nucleic acids with a firstoligonucleotide comprising a T_(m)-enhanced oligonucleotide to form amixture; and (b) isolating the desired template nucleic acid from themixture.
 26. The method of claim 25, wherein the step of contacting thepopulation of template nucleic acids with a first oligonucleotidecomprising a T_(m)-enhanced oligonucleotide comprises incubating themixture at a temperature of about optimal enhanced T_(m) value of theT_(m)-enhanced oligonucleotide.
 27. The method of claim 25, wherein theT_(m)-enhanced oligonucleotide comprises a plurality of T_(m)-enhancinggroups.
 28. The method of claim 26, wherein the plurality ofT_(m)-enhancing groups comprises from about 2 to about 25T_(m)-enhancing groups.
 29. The method of claim 26, wherein theplurality of T_(m)-enhancing groups comprises locked nucleic acid groupsor a bicyclic nucleic acid groups.
 30. The method of claim 29, whereinthe locked nucleic acid groups or the bicyclic nucleic acid groupscomprise nucleobases selected from the group consisting of cytosine,adenine and thymine.
 31. The method of claim 25, wherein theT_(m)-enhanced oligonucleotide comprises at least one member selectedfrom the group consisting of SEQ ID NOS: 2, 3, 4, 5, 6, 7, 8, 10, 11,12, 13, 14, 15, 16, 18, 19, 21, 22, 24, 25, 27, 28, 30, 32, 34 and 36.32. The method of claim 25, wherein the T_(m)-enhanced oligonucleotidecomprises a blocker.
 33. The method of claim 32, wherein the blocker hassubstantial sequence complementarity to at least one sequence at aterminus of each member of the population of template nucleic acids. 34.The method of claim 32, wherein the blocker further comprises a barcodedomain having a plurality of nucleotides.
 35. The method of claim 32,wherein the plurality of nucleotides comprises from about 5 to about 12nucleotides arranged substantially contiguous.
 36. The method of claim34, wherein the barcode domain comprises nucleotides having asnucleobases at least one member selected from the group selected fromadenine, thymine, cytosine, guanine, inosine, 3-nitropyrrole,5-nitroindole, and combinations thereof.
 37. The method of claim 25,wherein the step of contacting the population of template nucleic acidswith a first oligonucleotide comprising a T_(m)-enhancedoligonucleotides results in substantial inhibition of complex formationbetween the desired template nucleic acid and undesired template nucleicacids.
 38. The method of claim 25, wherein the step of isolating thedesired template nucleic acid comprises: (i) forming a hybrid complexbetween the desired nucleic acid and a second oligonucleotide; and (ii)separating the hybrid complex from the mixture.
 39. The method of claim38, wherein the second oligonucleotide comprises a bait.
 40. The methodof claim 39, wherein the bait comprises a sequence having substantialsequence complementarity to a sequence within the desired templatenucleic acid.
 41. The method of claim 39, wherein the bait comprises aplurality of T_(m)-enhancing groups.
 42. The method of claim 39, whereinthe bait includes a covalent modification to enable selection of thehybrid complex.
 43. The method of claim 42, wherein the covalentmodification is a biotinylated group.
 44. The method of claim 43,wherein the hybrid complex is contacted with a solid support immobilizedwith avidin or streptavidin.
 45. A method of performing massivelyparallel sequencing, comprising: (a) preparing a library population oftemplate nucleic acids; (b) contacting the library population oftemplate nucleic acids with at least one T_(m)-enhanced oligonucleotideas a blocker, a plurality of oligonucleotides as baits and C_(o)t-1 DNAto form a mixture; (c) isolating a plurality of desired template nucleicacids from the mixture; and (d) sequencing the plurality of desiredtemplate nucleic acids, wherein at least one member of the plurality ofoligonucleotides as baits has substantial sequence complementarity to asequence within at least one member of the plurality of desired templatenucleic acids.
 46. The method of claim 45, wherein members of thelibrary population of template nucleic acids each includes at least oneidentical terminal adaptor sequence having a size range from about 15nucleotides to about 75 nucleotides.
 47. The method of claim 46, whereinthe blocker has substantial sequence complementarity to the at least oneidentical terminal adaptor sequence of the library population oftemplate nucleic acids.
 48. The method of claim 46, wherein the at leastone identical terminal adaptor sequence includes a barcode domain. 49.The method of claim 48, wherein the blocker has substantial sequencecomplementarity to the at least one identical terminal adaptor sequence.50. The method of claim 47, wherein the contacting step (b) comprisesincubating the mixture at a temperature of about optimal enhanced T_(m)value of the at least one T_(m)-enhanced oligonucleotide.
 51. The methodof claim 45, wherein the at least one T_(m)-enhanced oligonucleotide asa blocker comprises at least one member selected from the groupconsisting of SEQ ID NOS: 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15,16, 18, 19, 21, 22, 24, 25, 27, 28, 30, 32, 34 and
 36. 52. The method ofclaim 45, wherein the step of isolating a plurality of desired templatenucleic acids from the mixture comprises: (i) forming a plurality ofhybrid complexes between the plurality of desired template nucleic acidsand plurality of oligonucleotides as baits; and (ii) separating theplurality of hybrid complexes from the mixture.
 53. The method of claim52, wherein the plurality of oligonucleotides as baits comprises aplurality of T_(m)-enhancing groups.
 54. The method of claim 52, whereineach bait includes a covalent modification to enable selection of thehybrid complex that includes the bait.
 55. The method of claim 54,wherein the covalent modification is a biotinylated group.
 56. Themethod of claim 55, wherein the plurality of hybrid complexes iscontacted with a solid support immobilized with avidin or streptavidin.57-80. (canceled)